- Descriptive Research Designs: Types, Examples & Methods
One of the components of research is getting enough information about the research problem—the what, how, when and where answers, which is why descriptive research is an important type of research. It is very useful when conducting research whose aim is to identify characteristics, frequencies, trends, correlations, and categories.
This research method takes a problem with little to no relevant information and gives it a befitting description using qualitative and quantitative research method s. Descriptive research aims to accurately describe a research problem.
In the subsequent sections, we will be explaining what descriptive research means, its types, examples, and data collection methods.
What is Descriptive Research?
Descriptive research is a type of research that describes a population, situation, or phenomenon that is being studied. It focuses on answering the how, what, when, and where questions If a research problem, rather than the why.
This is mainly because it is important to have a proper understanding of what a research problem is about before investigating why it exists in the first place.
For example, an investor considering an investment in the ever-changing Amsterdam housing market needs to understand what the current state of the market is, how it changes (increasing or decreasing), and when it changes (time of the year) before asking for the why. This is where descriptive research comes in.
What Are The Types of Descriptive Research?
Descriptive research is classified into different types according to the kind of approach that is used in conducting descriptive research. The different types of descriptive research are highlighted below:
- Descriptive-survey
Descriptive survey research uses surveys to gather data about varying subjects. This data aims to know the extent to which different conditions can be obtained among these subjects.
For example, a researcher wants to determine the qualification of employed professionals in Maryland. He uses a survey as his research instrument , and each item on the survey related to qualifications is subjected to a Yes/No answer.
This way, the researcher can describe the qualifications possessed by the employed demographics of this community.
- Descriptive-normative survey
This is an extension of the descriptive survey, with the addition being the normative element. In the descriptive-normative survey, the results of the study should be compared with the norm.
For example, an organization that wishes to test the skills of its employees by a team may have them take a skills test. The skills tests are the evaluation tool in this case, and the result of this test is compared with the norm of each role.
If the score of the team is one standard deviation above the mean, it is very satisfactory, if within the mean, satisfactory, and one standard deviation below the mean is unsatisfactory.
- Descriptive-status
This is a quantitative description technique that seeks to answer questions about real-life situations. For example, a researcher researching the income of the employees in a company, and the relationship with their performance.
A survey will be carried out to gather enough data about the income of the employees, then their performance will be evaluated and compared to their income. This will help determine whether a higher income means better performance and low income means lower performance or vice versa.
- Descriptive-analysis
The descriptive-analysis method of research describes a subject by further analyzing it, which in this case involves dividing it into 2 parts. For example, the HR personnel of a company that wishes to analyze the job role of each employee of the company may divide the employees into the people that work at the Headquarters in the US and those that work from Oslo, Norway office.
A questionnaire is devised to analyze the job role of employees with similar salaries and who work in similar positions.
- Descriptive classification
This method is employed in biological sciences for the classification of plants and animals. A researcher who wishes to classify the sea animals into different species will collect samples from various search stations, then classify them accordingly.
- Descriptive-comparative
In descriptive-comparative research, the researcher considers 2 variables that are not manipulated, and establish a formal procedure to conclude that one is better than the other. For example, an examination body wants to determine the better method of conducting tests between paper-based and computer-based tests.
A random sample of potential participants of the test may be asked to use the 2 different methods, and factors like failure rates, time factors, and others will be evaluated to arrive at the best method.
- Correlative Survey
Correlative surveys are used to determine whether the relationship between 2 variables is positive, negative, or neutral. That is, if 2 variables say X and Y are directly proportional, inversely proportional or are not related to each other.
Examples of Descriptive Research
There are different examples of descriptive research, that may be highlighted from its types, uses, and applications. However, we will be restricting ourselves to only 3 distinct examples in this article.
- Comparing Student Performance:
An academic institution may wish 2 compare the performance of its junior high school students in English language and Mathematics. This may be used to classify students based on 2 major groups, with one group going ahead to study while courses, while the other study courses in the Arts & Humanities field.
Students who are more proficient in mathematics will be encouraged to go into STEM and vice versa. Institutions may also use this data to identify students’ weak points and work on ways to assist them.
- Scientific Classification
During the major scientific classification of plants, animals, and periodic table elements, the characteristics and components of each subject are evaluated and used to determine how they are classified.
For example, living things may be classified into kingdom Plantae or kingdom animal is depending on their nature. Further classification may group animals into mammals, pieces, vertebrae, invertebrae, etc.
All these classifications are made a result of descriptive research which describes what they are.
- Human Behavior
When studying human behaviour based on a factor or event, the researcher observes the characteristics, behaviour, and reaction, then use it to conclude. A company willing to sell to its target market needs to first study the behaviour of the market.
This may be done by observing how its target reacts to a competitor’s product, then use it to determine their behaviour.
What are the Characteristics of Descriptive Research?
The characteristics of descriptive research can be highlighted from its definition, applications, data collection methods, and examples. Some characteristics of descriptive research are:
- Quantitativeness
Descriptive research uses a quantitative research method by collecting quantifiable information to be used for statistical analysis of the population sample. This is very common when dealing with research in the physical sciences.
- Qualitativeness
It can also be carried out using the qualitative research method, to properly describe the research problem. This is because descriptive research is more explanatory than exploratory or experimental.
- Uncontrolled variables
In descriptive research, researchers cannot control the variables like they do in experimental research.
- The basis for further research
The results of descriptive research can be further analyzed and used in other research methods. It can also inform the next line of research, including the research method that should be used.
This is because it provides basic information about the research problem, which may give birth to other questions like why a particular thing is the way it is.
Why Use Descriptive Research Design?
Descriptive research can be used to investigate the background of a research problem and get the required information needed to carry out further research. It is used in multiple ways by different organizations, and especially when getting the required information about their target audience.
- Define subject characteristics :
It is used to determine the characteristics of the subjects, including their traits, behaviour, opinion, etc. This information may be gathered with the use of surveys, which are shared with the respondents who in this case, are the research subjects.
For example, a survey evaluating the number of hours millennials in a community spends on the internet weekly, will help a service provider make informed business decisions regarding the market potential of the community.
- Measure Data Trends
It helps to measure the changes in data over some time through statistical methods. Consider the case of individuals who want to invest in stock markets, so they evaluate the changes in prices of the available stocks to make a decision investment decision.
Brokerage companies are however the ones who carry out the descriptive research process, while individuals can view the data trends and make decisions.
Descriptive research is also used to compare how different demographics respond to certain variables. For example, an organization may study how people with different income levels react to the launch of a new Apple phone.
This kind of research may take a survey that will help determine which group of individuals are purchasing the new Apple phone. Do the low-income earners also purchase the phone, or only the high-income earners do?
Further research using another technique will explain why low-income earners are purchasing the phone even though they can barely afford it. This will help inform strategies that will lure other low-income earners and increase company sales.
- Validate existing conditions
When you are not sure about the validity of an existing condition, you can use descriptive research to ascertain the underlying patterns of the research object. This is because descriptive research methods make an in-depth analysis of each variable before making conclusions.
- Conducted Overtime
Descriptive research is conducted over some time to ascertain the changes observed at each point in time. The higher the number of times it is conducted, the more authentic the conclusion will be.
What are the Disadvantages of Descriptive Research?
- Response and Non-response Bias
Respondents may either decide not to respond to questions or give incorrect responses if they feel the questions are too confidential. When researchers use observational methods, respondents may also decide to behave in a particular manner because they feel they are being watched.
- The researcher may decide to influence the result of the research due to personal opinion or bias towards a particular subject. For example, a stockbroker who also has a business of his own may try to lure investors into investing in his own company by manipulating results.
- A case-study or sample taken from a large population is not representative of the whole population.
- Limited scope:The scope of descriptive research is limited to the what of research, with no information on why thereby limiting the scope of the research.
What are the Data Collection Methods in Descriptive Research?
There are 3 main data collection methods in descriptive research, namely; observational method, case study method, and survey research.
1. Observational Method
The observational method allows researchers to collect data based on their view of the behaviour and characteristics of the respondent, with the respondents themselves not directly having an input. It is often used in market research, psychology, and some other social science research to understand human behaviour.
It is also an important aspect of physical scientific research, with it being one of the most effective methods of conducting descriptive research . This process can be said to be either quantitative or qualitative.
Quantitative observation involved the objective collection of numerical data , whose results can be analyzed using numerical and statistical methods.
Qualitative observation, on the other hand, involves the monitoring of characteristics and not the measurement of numbers. The researcher makes his observation from a distance, records it, and is used to inform conclusions.
2. Case Study Method
A case study is a sample group (an individual, a group of people, organizations, events, etc.) whose characteristics are used to describe the characteristics of a larger group in which the case study is a subgroup. The information gathered from investigating a case study may be generalized to serve the larger group.
This generalization, may, however, be risky because case studies are not sufficient to make accurate predictions about larger groups. Case studies are a poor case of generalization.
3. Survey Research
This is a very popular data collection method in research designs. In survey research, researchers create a survey or questionnaire and distribute it to respondents who give answers.
Generally, it is used to obtain quick information directly from the primary source and also conducting rigorous quantitative and qualitative research. In some cases, survey research uses a blend of both qualitative and quantitative strategies.
Survey research can be carried out both online and offline using the following methods
- Online Surveys: This is a cheap method of carrying out surveys and getting enough responses. It can be carried out using Formplus, an online survey builder. Formplus has amazing tools and features that will help increase response rates.
- Offline Surveys: This includes paper forms, mobile offline forms , and SMS-based forms.
What Are The Differences Between Descriptive and Correlational Research?
Before going into the differences between descriptive and correlation research, we need to have a proper understanding of what correlation research is about. Therefore, we will be giving a summary of the correlation research below.
Correlational research is a type of descriptive research, which is used to measure the relationship between 2 variables, with the researcher having no control over them. It aims to find whether there is; positive correlation (both variables change in the same direction), negative correlation (the variables change in the opposite direction), or zero correlation (there is no relationship between the variables).
Correlational research may be used in 2 situations;
(i) when trying to find out if there is a relationship between two variables, and
(ii) when a causal relationship is suspected between two variables, but it is impractical or unethical to conduct experimental research that manipulates one of the variables.
Below are some of the differences between correlational and descriptive research:
- Definitions :
Descriptive research aims is a type of research that provides an in-depth understanding of the study population, while correlational research is the type of research that measures the relationship between 2 variables.
- Characteristics :
Descriptive research provides descriptive data explaining what the research subject is about, while correlation research explores the relationship between data and not their description.
- Predictions :
Predictions cannot be made in descriptive research while correlation research accommodates the possibility of making predictions.
Descriptive Research vs. Causal Research
Descriptive research and causal research are both research methodologies, however, one focuses on a subject’s behaviors while the latter focuses on a relationship’s cause-and-effect. To buttress the above point, descriptive research aims to describe and document the characteristics, behaviors, or phenomena of a particular or specific population or situation.
It focuses on providing an accurate and detailed account of an already existing state of affairs between variables. Descriptive research answers the questions of “what,” “where,” “when,” and “how” without attempting to establish any causal relationships or explain any underlying factors that might have caused the behavior.
Causal research, on the other hand, seeks to determine cause-and-effect relationships between variables. It aims to point out the factors that influence or cause a particular result or behavior. Causal research involves manipulating variables, controlling conditions or a subgroup, and observing the resulting effects. The primary objective of causal research is to establish a cause-effect relationship and provide insights into why certain phenomena happen the way they do.
Descriptive Research vs. Analytical Research
Descriptive research provides a detailed and comprehensive account of a specific situation or phenomenon. It focuses on describing and summarizing data without making inferences or attempting to explain underlying factors or the cause of the factor.
It is primarily concerned with providing an accurate and objective representation of the subject of research. While analytical research goes beyond the description of the phenomena and seeks to analyze and interpret data to discover if there are patterns, relationships, or any underlying factors.
It examines the data critically, applies statistical techniques or other analytical methods, and draws conclusions based on the discovery. Analytical research also aims to explore the relationships between variables and understand the underlying mechanisms or processes involved.
Descriptive Research vs. Exploratory Research
Descriptive research is a research method that focuses on providing a detailed and accurate account of a specific situation, group, or phenomenon. This type of research describes the characteristics, behaviors, or relationships within the given context without looking for an underlying cause.
Descriptive research typically involves collecting and analyzing quantitative or qualitative data to generate descriptive statistics or narratives. Exploratory research differs from descriptive research because it aims to explore and gain firsthand insights or knowledge into a relatively unexplored or poorly understood topic.
It focuses on generating ideas, hypotheses, or theories rather than providing definitive answers. Exploratory research is often conducted at the early stages of a research project to gather preliminary information and identify key variables or factors for further investigation. It involves open-ended interviews, observations, or small-scale surveys to gather qualitative data.
Read More – Exploratory Research: What are its Method & Examples?
Descriptive Research vs. Experimental Research
Descriptive research aims to describe and document the characteristics, behaviors, or phenomena of a particular population or situation. It focuses on providing an accurate and detailed account of the existing state of affairs.
Descriptive research typically involves collecting data through surveys, observations, or existing records and analyzing the data to generate descriptive statistics or narratives. It does not involve manipulating variables or establishing cause-and-effect relationships.
Experimental research, on the other hand, involves manipulating variables and controlling conditions to investigate cause-and-effect relationships. It aims to establish causal relationships by introducing an intervention or treatment and observing the resulting effects.
Experimental research typically involves randomly assigning participants to different groups, such as control and experimental groups, and measuring the outcomes. It allows researchers to control for confounding variables and draw causal conclusions.
Related – Experimental vs Non-Experimental Research: 15 Key Differences
Descriptive Research vs. Explanatory Research
Descriptive research focuses on providing a detailed and accurate account of a specific situation, group, or phenomenon. It aims to describe the characteristics, behaviors, or relationships within the given context.
Descriptive research is primarily concerned with providing an objective representation of the subject of study without explaining underlying causes or mechanisms. Explanatory research seeks to explain the relationships between variables and uncover the underlying causes or mechanisms.
It goes beyond description and aims to understand the reasons or factors that influence a particular outcome or behavior. Explanatory research involves analyzing data, conducting statistical analyses, and developing theories or models to explain the observed relationships.
Descriptive Research vs. Inferential Research
Descriptive research focuses on describing and summarizing data without making inferences or generalizations beyond the specific sample or population being studied. It aims to provide an accurate and objective representation of the subject of study.
Descriptive research typically involves analyzing data to generate descriptive statistics, such as means, frequencies, or percentages, to describe the characteristics or behaviors observed.
Inferential research, however, involves making inferences or generalizations about a larger population based on a smaller sample.
It aims to draw conclusions about the population characteristics or relationships by analyzing the sample data. Inferential research uses statistical techniques to estimate population parameters, test hypotheses, and determine the level of confidence or significance in the findings.
Related – Inferential Statistics: Definition, Types + Examples
Conclusion
The uniqueness of descriptive research partly lies in its ability to explore both quantitative and qualitative research methods. Therefore, when conducting descriptive research, researchers have the opportunity to use a wide variety of techniques that aids the research process.
Descriptive research explores research problems in-depth, beyond the surface level thereby giving a detailed description of the research subject. That way, it can aid further research in the field, including other research methods .
It is also very useful in solving real-life problems in various fields of social science, physical science, and education.
Connect to Formplus, Get Started Now - It's Free!
- descriptive research
- descriptive research method
- example of descriptive research
- types of descriptive research
- busayo.longe
You may also like:
Acceptance Sampling: Meaning, Examples, When to Use
In this post, we will discuss extensively what acceptance sampling is and when it is applied.
Type I vs Type II Errors: Causes, Examples & Prevention
This article will discuss the two different types of errors in hypothesis testing and how you can prevent them from occurring in your research
Cross-Sectional Studies: Types, Pros, Cons & Uses
In this article, we’ll look at what cross-sectional studies are, how it applies to your research and how to use Formplus to collect...
Extrapolation in Statistical Research: Definition, Examples, Types, Applications
In this article we’ll look at the different types and characteristics of extrapolation, plus how it contrasts to interpolation.
Formplus - For Seamless Data Collection
Collect data the right way with a versatile data collection tool. try formplus and transform your work productivity today..
- What is descriptive research?
Last updated
5 February 2023
Reviewed by
Cathy Heath
Short on time? Get an AI generated summary of this article instead
Descriptive research is a common investigatory model used by researchers in various fields, including social sciences, linguistics, and academia.
Read on to understand the characteristics of descriptive research and explore its underlying techniques, processes, and procedures.
Analyze your descriptive research
Dovetail streamlines analysis to help you uncover and share actionable insights
Descriptive research is an exploratory research method. It enables researchers to precisely and methodically describe a population, circumstance, or phenomenon.
As the name suggests, descriptive research describes the characteristics of the group, situation, or phenomenon being studied without manipulating variables or testing hypotheses . This can be reported using surveys , observational studies, and case studies. You can use both quantitative and qualitative methods to compile the data.
Besides making observations and then comparing and analyzing them, descriptive studies often develop knowledge concepts and provide solutions to critical issues. It always aims to answer how the event occurred, when it occurred, where it occurred, and what the problem or phenomenon is.
- Characteristics of descriptive research
The following are some of the characteristics of descriptive research:
Quantitativeness
Descriptive research can be quantitative as it gathers quantifiable data to statistically analyze a population sample. These numbers can show patterns, connections, and trends over time and can be discovered using surveys, polls, and experiments.
Qualitativeness
Descriptive research can also be qualitative. It gives meaning and context to the numbers supplied by quantitative descriptive research .
Researchers can use tools like interviews, focus groups, and ethnographic studies to illustrate why things are what they are and help characterize the research problem. This is because it’s more explanatory than exploratory or experimental research.
Uncontrolled variables
Descriptive research differs from experimental research in that researchers cannot manipulate the variables. They are recognized, scrutinized, and quantified instead. This is one of its most prominent features.
Cross-sectional studies
Descriptive research is a cross-sectional study because it examines several areas of the same group. It involves obtaining data on multiple variables at the personal level during a certain period. It’s helpful when trying to understand a larger community’s habits or preferences.
Carried out in a natural environment
Descriptive studies are usually carried out in the participants’ everyday environment, which allows researchers to avoid influencing responders by collecting data in a natural setting. You can use online surveys or survey questions to collect data or observe.
Basis for further research
You can further dissect descriptive research’s outcomes and use them for different types of investigation. The outcomes also serve as a foundation for subsequent investigations and can guide future studies. For example, you can use the data obtained in descriptive research to help determine future research designs.
- Descriptive research methods
There are three basic approaches for gathering data in descriptive research: observational, case study, and survey.
You can use surveys to gather data in descriptive research. This involves gathering information from many people using a questionnaire and interview .
Surveys remain the dominant research tool for descriptive research design. Researchers can conduct various investigations and collect multiple types of data (quantitative and qualitative) using surveys with diverse designs.
You can conduct surveys over the phone, online, or in person. Your survey might be a brief interview or conversation with a set of prepared questions intended to obtain quick information from the primary source.
Observation
This descriptive research method involves observing and gathering data on a population or phenomena without manipulating variables. It is employed in psychology, market research , and other social science studies to track and understand human behavior.
Observation is an essential component of descriptive research. It entails gathering data and analyzing it to see whether there is a relationship between the two variables in the study. This strategy usually allows for both qualitative and quantitative data analysis.
Case studies
A case study can outline a specific topic’s traits. The topic might be a person, group, event, or organization.
It involves using a subset of a larger group as a sample to characterize the features of that larger group.
You can generalize knowledge gained from studying a case study to benefit a broader audience.
This approach entails carefully examining a particular group, person, or event over time. You can learn something new about the study topic by using a small group to better understand the dynamics of the entire group.
- Types of descriptive research
There are several types of descriptive study. The most well-known include cross-sectional studies, census surveys, sample surveys, case reports, and comparison studies.
Case reports and case series
In the healthcare and medical fields, a case report is used to explain a patient’s circumstances when suffering from an uncommon illness or displaying certain symptoms. Case reports and case series are both collections of related cases. They have aided the advancement of medical knowledge on countless occasions.
The normative component is an addition to the descriptive survey. In the descriptive–normative survey, you compare the study’s results to the norm.
Descriptive survey
This descriptive type of research employs surveys to collect information on various topics. This data aims to determine the degree to which certain conditions may be attained.
You can extrapolate or generalize the information you obtain from sample surveys to the larger group being researched.
Correlative survey
Correlative surveys help establish if there is a positive, negative, or neutral connection between two variables.
Performing census surveys involves gathering relevant data on several aspects of a given population. These units include individuals, families, organizations, objects, characteristics, and properties.
During descriptive research, you gather different degrees of interest over time from a specific population. Cross-sectional studies provide a glimpse of a phenomenon’s prevalence and features in a population. There are no ethical challenges with them and they are quite simple and inexpensive to carry out.
Comparative studies
These surveys compare the two subjects’ conditions or characteristics. The subjects may include research variables, organizations, plans, and people.
Comparison points, assumption of similarities, and criteria of comparison are three important variables that affect how well and accurately comparative studies are conducted.
For instance, descriptive research can help determine how many CEOs hold a bachelor’s degree and what proportion of low-income households receive government help.
- Pros and cons
The primary advantage of descriptive research designs is that researchers can create a reliable and beneficial database for additional study. To conduct any inquiry, you need access to reliable information sources that can give you a firm understanding of a situation.
Quantitative studies are time- and resource-intensive, so knowing the hypotheses viable for testing is crucial. The basic overview of descriptive research provides helpful hints as to which variables are worth quantitatively examining. This is why it’s employed as a precursor to quantitative research designs.
Some experts view this research as untrustworthy and unscientific. However, there is no way to assess the findings because you don’t manipulate any variables statistically.
Cause-and-effect correlations also can’t be established through descriptive investigations. Additionally, observational study findings cannot be replicated, which prevents a review of the findings and their replication.
The absence of statistical and in-depth analysis and the rather superficial character of the investigative procedure are drawbacks of this research approach.
- Descriptive research examples and applications
Several descriptive research examples are emphasized based on their types, purposes, and applications. Research questions often begin with “What is …” These studies help find solutions to practical issues in social science, physical science, and education.
Here are some examples and applications of descriptive research:
Determining consumer perception and behavior
Organizations use descriptive research designs to determine how various demographic groups react to a certain product or service.
For example, a business looking to sell to its target market should research the market’s behavior first. When researching human behavior in response to a cause or event, the researcher pays attention to the traits, actions, and responses before drawing a conclusion.
Scientific classification
Scientific descriptive research enables the classification of organisms and their traits and constituents.
Measuring data trends
A descriptive study design’s statistical capabilities allow researchers to track data trends over time. It’s frequently used to determine the study target’s current circumstances and underlying patterns.
Conduct comparison
Organizations can use a descriptive research approach to learn how various demographics react to a certain product or service. For example, you can study how the target market responds to a competitor’s product and use that information to infer their behavior.
- Bottom line
A descriptive research design is suitable for exploring certain topics and serving as a prelude to larger quantitative investigations. It provides a comprehensive understanding of the “what” of the group or thing you’re investigating.
This research type acts as the cornerstone of other research methodologies . It is distinctive because it can use quantitative and qualitative research approaches at the same time.
What is descriptive research design?
Descriptive research design aims to systematically obtain information to describe a phenomenon, situation, or population. More specifically, it helps answer the what, when, where, and how questions regarding the research problem rather than the why.
How does descriptive research compare to qualitative research?
Despite certain parallels, descriptive research concentrates on describing phenomena, while qualitative research aims to understand people better.
How do you analyze descriptive research data?
Data analysis involves using various methodologies, enabling the researcher to evaluate and provide results regarding validity and reliability.
Should you be using a customer insights hub?
Do you want to discover previous research faster?
Do you share your research findings with others?
Do you analyze research data?
Start for free today, add your research, and get to key insights faster
Editor’s picks
Last updated: 18 April 2023
Last updated: 27 February 2023
Last updated: 6 February 2023
Last updated: 6 October 2023
Last updated: 5 February 2023
Last updated: 16 April 2023
Last updated: 9 March 2023
Last updated: 12 December 2023
Last updated: 11 March 2024
Last updated: 4 July 2024
Last updated: 6 March 2024
Last updated: 5 March 2024
Last updated: 13 May 2024
Latest articles
Related topics, .css-je19u9{-webkit-align-items:flex-end;-webkit-box-align:flex-end;-ms-flex-align:flex-end;align-items:flex-end;display:-webkit-box;display:-webkit-flex;display:-ms-flexbox;display:flex;-webkit-flex-direction:row;-ms-flex-direction:row;flex-direction:row;-webkit-box-flex-wrap:wrap;-webkit-flex-wrap:wrap;-ms-flex-wrap:wrap;flex-wrap:wrap;-webkit-box-pack:center;-ms-flex-pack:center;-webkit-justify-content:center;justify-content:center;row-gap:0;text-align:center;max-width:671px;}@media (max-width: 1079px){.css-je19u9{max-width:400px;}.css-je19u9>span{white-space:pre;}}@media (max-width: 799px){.css-je19u9{max-width:400px;}.css-je19u9>span{white-space:pre;}} decide what to .css-1kiodld{max-height:56px;display:-webkit-box;display:-webkit-flex;display:-ms-flexbox;display:flex;-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;}@media (max-width: 1079px){.css-1kiodld{display:none;}} build next, decide what to build next.
Users report unexpectedly high data usage, especially during streaming sessions.
Users find it hard to navigate from the home page to relevant playlists in the app.
It would be great to have a sleep timer feature, especially for bedtime listening.
I need better filters to find the songs or artists I’m looking for.
Log in or sign up
Get started for free
Want to create or adapt books like this? Learn more about how Pressbooks supports open publishing practices.
Chapter 3. Psychological Science
3.2 Psychologists Use Descriptive, Correlational, and Experimental Research Designs to Understand Behaviour
Learning objectives.
- Differentiate the goals of descriptive, correlational, and experimental research designs and explain the advantages and disadvantages of each.
- Explain the goals of descriptive research and the statistical techniques used to interpret it.
- Summarize the uses of correlational research and describe why correlational research cannot be used to infer causality.
- Review the procedures of experimental research and explain how it can be used to draw causal inferences.
Psychologists agree that if their ideas and theories about human behaviour are to be taken seriously, they must be backed up by data. However, the research of different psychologists is designed with different goals in mind, and the different goals require different approaches. These varying approaches, summarized in Table 3.2, are known as research designs . A research design is the specific method a researcher uses to collect, analyze, and interpret data . Psychologists use three major types of research designs in their research, and each provides an essential avenue for scientific investigation. Descriptive research is research designed to provide a snapshot of the current state of affairs . Correlational research is research designed to discover relationships among variables and to allow the prediction of future events from present knowledge . Experimental research is research in which initial equivalence among research participants in more than one group is created, followed by a manipulation of a given experience for these groups and a measurement of the influence of the manipulation . Each of the three research designs varies according to its strengths and limitations, and it is important to understand how each differs.
Research design | Goal | Advantages | Disadvantages |
---|---|---|---|
Descriptive | To create a snapshot of the current state of affairs | Provides a relatively complete picture of what is occurring at a given time. Allows the development of questions for further study. | Does not assess relationships among variables. May be unethical if participants do not know they are being observed. |
Correlational | To assess the relationships between and among two or more variables | Allows testing of expected relationships between and among variables and the making of predictions. Can assess these relationships in everyday life events. | Cannot be used to draw inferences about the causal relationships between and among the variables. |
Experimental | To assess the causal impact of one or more experimental manipulations on a dependent variable | Allows drawing of conclusions about the causal relationships among variables. | Cannot experimentally manipulate many important variables. May be expensive and time consuming. |
Source: Stangor, 2011. |
Descriptive Research: Assessing the Current State of Affairs
Descriptive research is designed to create a snapshot of the current thoughts, feelings, or behaviour of individuals. This section reviews three types of descriptive research : case studies , surveys , and naturalistic observation (Figure 3.4).
Sometimes the data in a descriptive research project are based on only a small set of individuals, often only one person or a single small group. These research designs are known as case studies — descriptive records of one or more individual’s experiences and behaviour . Sometimes case studies involve ordinary individuals, as when developmental psychologist Jean Piaget used his observation of his own children to develop his stage theory of cognitive development. More frequently, case studies are conducted on individuals who have unusual or abnormal experiences or characteristics or who find themselves in particularly difficult or stressful situations. The assumption is that by carefully studying individuals who are socially marginal, who are experiencing unusual situations, or who are going through a difficult phase in their lives, we can learn something about human nature.
Sigmund Freud was a master of using the psychological difficulties of individuals to draw conclusions about basic psychological processes. Freud wrote case studies of some of his most interesting patients and used these careful examinations to develop his important theories of personality. One classic example is Freud’s description of “Little Hans,” a child whose fear of horses the psychoanalyst interpreted in terms of repressed sexual impulses and the Oedipus complex (Freud, 1909/1964).
Another well-known case study is Phineas Gage, a man whose thoughts and emotions were extensively studied by cognitive psychologists after a railroad spike was blasted through his skull in an accident. Although there are questions about the interpretation of this case study (Kotowicz, 2007), it did provide early evidence that the brain’s frontal lobe is involved in emotion and morality (Damasio et al., 2005). An interesting example of a case study in clinical psychology is described by Rokeach (1964), who investigated in detail the beliefs of and interactions among three patients with schizophrenia, all of whom were convinced they were Jesus Christ.
In other cases the data from descriptive research projects come in the form of a survey — a measure administered through either an interview or a written questionnaire to get a picture of the beliefs or behaviours of a sample of people of interest . The people chosen to participate in the research (known as the sample) are selected to be representative of all the people that the researcher wishes to know about (the population). In election polls, for instance, a sample is taken from the population of all “likely voters” in the upcoming elections.
The results of surveys may sometimes be rather mundane, such as “Nine out of 10 doctors prefer Tymenocin” or “The median income in the city of Hamilton is $46,712.” Yet other times (particularly in discussions of social behaviour), the results can be shocking: “More than 40,000 people are killed by gunfire in the United States every year” or “More than 60% of women between the ages of 50 and 60 suffer from depression.” Descriptive research is frequently used by psychologists to get an estimate of the prevalence (or incidence ) of psychological disorders.
A final type of descriptive research — known as naturalistic observation — is research based on the observation of everyday events . For instance, a developmental psychologist who watches children on a playground and describes what they say to each other while they play is conducting descriptive research, as is a biopsychologist who observes animals in their natural habitats. One example of observational research involves a systematic procedure known as the strange situation , used to get a picture of how adults and young children interact. The data that are collected in the strange situation are systematically coded in a coding sheet such as that shown in Table 3.3.
Coder name: | ||||
This table represents a sample coding sheet from an episode of the “strange situation,” in which an infant (usually about one year old) is observed playing in a room with two adults — the child’s mother and a stranger. Each of the four coding categories is scored by the coder from 1 (the baby makes no effort to engage in the behaviour) to 7 (the baby makes a significant effort to engage in the behaviour). More information about the meaning of the coding can be found in Ainsworth, Blehar, Waters, and Wall (1978). | ||||
Coding categories explained | ||||
Proximity | The baby moves toward, grasps, or climbs on the adult. | |||
Maintaining contact | The baby resists being put down by the adult by crying or trying to climb back up. | |||
Resistance | The baby pushes, hits, or squirms to be put down from the adult’s arms. | |||
Avoidance | The baby turns away or moves away from the adult. | |||
Episode | Coding categories | |||
---|---|---|---|---|
Proximity | Contact | Resistance | Avoidance | |
Mother and baby play alone | 1 | 1 | 1 | 1 |
Mother puts baby down | 4 | 1 | 1 | 1 |
Stranger enters room | 1 | 2 | 3 | 1 |
Mother leaves room; stranger plays with baby | 1 | 3 | 1 | 1 |
Mother re-enters, greets and may comfort baby, then leaves again | 4 | 2 | 1 | 2 |
Stranger tries to play with baby | 1 | 3 | 1 | 1 |
Mother re-enters and picks up baby | 6 | 6 | 1 | 2 |
Source: Stang0r, 2011. |
The results of descriptive research projects are analyzed using descriptive statistics — numbers that summarize the distribution of scores on a measured variable . Most variables have distributions similar to that shown in Figure 3.5 where most of the scores are located near the centre of the distribution, and the distribution is symmetrical and bell-shaped. A data distribution that is shaped like a bell is known as a normal distribution .
A distribution can be described in terms of its central tendency — that is, the point in the distribution around which the data are centred — and its dispersion, or spread . The arithmetic average, or arithmetic mean , symbolized by the letter M , is the most commonly used measure of central tendency . It is computed by calculating the sum of all the scores of the variable and dividing this sum by the number of participants in the distribution (denoted by the letter N ). In the data presented in Figure 3.5 the mean height of the students is 67.12 inches (170.5 cm). The sample mean is usually indicated by the letter M .
In some cases, however, the data distribution is not symmetrical. This occurs when there are one or more extreme scores (known as outliers ) at one end of the distribution. Consider, for instance, the variable of family income (see Figure 3.6), which includes an outlier (a value of $3,800,000). In this case the mean is not a good measure of central tendency. Although it appears from Figure 3.6 that the central tendency of the family income variable should be around $70,000, the mean family income is actually $223,960. The single very extreme income has a disproportionate impact on the mean, resulting in a value that does not well represent the central tendency.
The median is used as an alternative measure of central tendency when distributions are not symmetrical. The median is the score in the center of the distribution, meaning that 50% of the scores are greater than the median and 50% of the scores are less than the median . In our case, the median household income ($73,000) is a much better indication of central tendency than is the mean household income ($223,960).
A final measure of central tendency, known as the mode , represents the value that occurs most frequently in the distribution . You can see from Figure 3.6 that the mode for the family income variable is $93,000 (it occurs four times).
In addition to summarizing the central tendency of a distribution, descriptive statistics convey information about how the scores of the variable are spread around the central tendency. Dispersion refers to the extent to which the scores are all tightly clustered around the central tendency , as seen in Figure 3.7.
Or they may be more spread out away from it, as seen in Figure 3.8.
One simple measure of dispersion is to find the largest (the maximum ) and the smallest (the minimum ) observed values of the variable and to compute the range of the variable as the maximum observed score minus the minimum observed score. You can check that the range of the height variable in Figure 3.5 is 72 – 62 = 10. The standard deviation , symbolized as s , is the most commonly used measure of dispersion . Distributions with a larger standard deviation have more spread. The standard deviation of the height variable is s = 2.74, and the standard deviation of the family income variable is s = $745,337.
An advantage of descriptive research is that it attempts to capture the complexity of everyday behaviour. Case studies provide detailed information about a single person or a small group of people, surveys capture the thoughts or reported behaviours of a large population of people, and naturalistic observation objectively records the behaviour of people or animals as it occurs naturally. Thus descriptive research is used to provide a relatively complete understanding of what is currently happening.
Despite these advantages, descriptive research has a distinct disadvantage in that, although it allows us to get an idea of what is currently happening, it is usually limited to static pictures. Although descriptions of particular experiences may be interesting, they are not always transferable to other individuals in other situations, nor do they tell us exactly why specific behaviours or events occurred. For instance, descriptions of individuals who have suffered a stressful event, such as a war or an earthquake, can be used to understand the individuals’ reactions to the event but cannot tell us anything about the long-term effects of the stress. And because there is no comparison group that did not experience the stressful situation, we cannot know what these individuals would be like if they hadn’t had the stressful experience.
Correlational Research: Seeking Relationships among Variables
In contrast to descriptive research, which is designed primarily to provide static pictures, correlational research involves the measurement of two or more relevant variables and an assessment of the relationship between or among those variables. For instance, the variables of height and weight are systematically related (correlated) because taller people generally weigh more than shorter people. In the same way, study time and memory errors are also related, because the more time a person is given to study a list of words, the fewer errors he or she will make. When there are two variables in the research design, one of them is called the predictor variable and the other the outcome variable . The research design can be visualized as shown in Figure 3.9, where the curved arrow represents the expected correlation between these two variables.
One way of organizing the data from a correlational study with two variables is to graph the values of each of the measured variables using a scatter plot . As you can see in Figure 3.10 a scatter plot is a visual image of the relationship between two variables . A point is plotted for each individual at the intersection of his or her scores for the two variables. When the association between the variables on the scatter plot can be easily approximated with a straight line , as in parts (a) and (b) of Figure 3.10 the variables are said to have a linear relationship .
When the straight line indicates that individuals who have above-average values for one variable also tend to have above-average values for the other variable , as in part (a), the relationship is said to be positive linear . Examples of positive linear relationships include those between height and weight, between education and income, and between age and mathematical abilities in children. In each case, people who score higher on one of the variables also tend to score higher on the other variable. Negative linear relationships , in contrast, as shown in part (b), occur when above-average values for one variable tend to be associated with below-average values for the other variable. Examples of negative linear relationships include those between the age of a child and the number of diapers the child uses, and between practice on and errors made on a learning task. In these cases, people who score higher on one of the variables tend to score lower on the other variable.
Relationships between variables that cannot be described with a straight line are known as nonlinear relationships . Part (c) of Figure 3.10 shows a common pattern in which the distribution of the points is essentially random. In this case there is no relationship at all between the two variables, and they are said to be independent . Parts (d) and (e) of Figure 3.10 show patterns of association in which, although there is an association, the points are not well described by a single straight line. For instance, part (d) shows the type of relationship that frequently occurs between anxiety and performance. Increases in anxiety from low to moderate levels are associated with performance increases, whereas increases in anxiety from moderate to high levels are associated with decreases in performance. Relationships that change in direction and thus are not described by a single straight line are called curvilinear relationships .
The most common statistical measure of the strength of linear relationships among variables is the Pearson correlation coefficient , which is symbolized by the letter r . The value of the correlation coefficient ranges from r = –1.00 to r = +1.00. The direction of the linear relationship is indicated by the sign of the correlation coefficient. Positive values of r (such as r = .54 or r = .67) indicate that the relationship is positive linear (i.e., the pattern of the dots on the scatter plot runs from the lower left to the upper right), whereas negative values of r (such as r = –.30 or r = –.72) indicate negative linear relationships (i.e., the dots run from the upper left to the lower right). The strength of the linear relationship is indexed by the distance of the correlation coefficient from zero (its absolute value). For instance, r = –.54 is a stronger relationship than r = .30, and r = .72 is a stronger relationship than r = –.57. Because the Pearson correlation coefficient only measures linear relationships, variables that have curvilinear relationships are not well described by r , and the observed correlation will be close to zero.
It is also possible to study relationships among more than two measures at the same time. A research design in which more than one predictor variable is used to predict a single outcome variable is analyzed through multiple regression (Aiken & West, 1991). Multiple regression is a statistical technique, based on correlation coefficients among variables, that allows predicting a single outcome variable from more than one predictor variable . For instance, Figure 3.11 shows a multiple regression analysis in which three predictor variables (Salary, job satisfaction, and years employed) are used to predict a single outcome (job performance). The use of multiple regression analysis shows an important advantage of correlational research designs — they can be used to make predictions about a person’s likely score on an outcome variable (e.g., job performance) based on knowledge of other variables.
An important limitation of correlational research designs is that they cannot be used to draw conclusions about the causal relationships among the measured variables. Consider, for instance, a researcher who has hypothesized that viewing violent behaviour will cause increased aggressive play in children. He has collected, from a sample of Grade 4 children, a measure of how many violent television shows each child views during the week, as well as a measure of how aggressively each child plays on the school playground. From his collected data, the researcher discovers a positive correlation between the two measured variables.
Although this positive correlation appears to support the researcher’s hypothesis, it cannot be taken to indicate that viewing violent television causes aggressive behaviour. Although the researcher is tempted to assume that viewing violent television causes aggressive play, there are other possibilities. One alternative possibility is that the causal direction is exactly opposite from what has been hypothesized. Perhaps children who have behaved aggressively at school develop residual excitement that leads them to want to watch violent television shows at home (Figure 3.13):
Although this possibility may seem less likely, there is no way to rule out the possibility of such reverse causation on the basis of this observed correlation. It is also possible that both causal directions are operating and that the two variables cause each other (Figure 3.14).
Still another possible explanation for the observed correlation is that it has been produced by the presence of a common-causal variable (also known as a third variable ). A common-causal variable is a variable that is not part of the research hypothesis but that causes both the predictor and the outcome variable and thus produces the observed correlation between them . In our example, a potential common-causal variable is the discipline style of the children’s parents. Parents who use a harsh and punitive discipline style may produce children who like to watch violent television and who also behave aggressively in comparison to children whose parents use less harsh discipline (Figure 3.15)
In this case, television viewing and aggressive play would be positively correlated (as indicated by the curved arrow between them), even though neither one caused the other but they were both caused by the discipline style of the parents (the straight arrows). When the predictor and outcome variables are both caused by a common-causal variable, the observed relationship between them is said to be spurious . A spurious relationship is a relationship between two variables in which a common-causal variable produces and “explains away” the relationship . If effects of the common-causal variable were taken away, or controlled for, the relationship between the predictor and outcome variables would disappear. In the example, the relationship between aggression and television viewing might be spurious because by controlling for the effect of the parents’ disciplining style, the relationship between television viewing and aggressive behaviour might go away.
Common-causal variables in correlational research designs can be thought of as mystery variables because, as they have not been measured, their presence and identity are usually unknown to the researcher. Since it is not possible to measure every variable that could cause both the predictor and outcome variables, the existence of an unknown common-causal variable is always a possibility. For this reason, we are left with the basic limitation of correlational research: correlation does not demonstrate causation. It is important that when you read about correlational research projects, you keep in mind the possibility of spurious relationships, and be sure to interpret the findings appropriately. Although correlational research is sometimes reported as demonstrating causality without any mention being made of the possibility of reverse causation or common-causal variables, informed consumers of research, like you, are aware of these interpretational problems.
In sum, correlational research designs have both strengths and limitations. One strength is that they can be used when experimental research is not possible because the predictor variables cannot be manipulated. Correlational designs also have the advantage of allowing the researcher to study behaviour as it occurs in everyday life. And we can also use correlational designs to make predictions — for instance, to predict from the scores on their battery of tests the success of job trainees during a training session. But we cannot use such correlational information to determine whether the training caused better job performance. For that, researchers rely on experiments.
Experimental Research: Understanding the Causes of Behaviour
The goal of experimental research design is to provide more definitive conclusions about the causal relationships among the variables in the research hypothesis than is available from correlational designs. In an experimental research design, the variables of interest are called the independent variable (or variables ) and the dependent variable . The independent variable in an experiment is the causing variable that is created (manipulated) by the experimenter . The dependent variable in an experiment is a measured variable that is expected to be influenced by the experimental manipulation . The research hypothesis suggests that the manipulated independent variable or variables will cause changes in the measured dependent variables. We can diagram the research hypothesis by using an arrow that points in one direction. This demonstrates the expected direction of causality (Figure 3.16):
Research Focus: Video Games and Aggression
Consider an experiment conducted by Anderson and Dill (2000). The study was designed to test the hypothesis that viewing violent video games would increase aggressive behaviour. In this research, male and female undergraduates from Iowa State University were given a chance to play with either a violent video game (Wolfenstein 3D) or a nonviolent video game (Myst). During the experimental session, the participants played their assigned video games for 15 minutes. Then, after the play, each participant played a competitive game with an opponent in which the participant could deliver blasts of white noise through the earphones of the opponent. The operational definition of the dependent variable (aggressive behaviour) was the level and duration of noise delivered to the opponent. The design of the experiment is shown in Figure 3.17
Two advantages of the experimental research design are (a) the assurance that the independent variable (also known as the experimental manipulation ) occurs prior to the measured dependent variable, and (b) the creation of initial equivalence between the conditions of the experiment (in this case by using random assignment to conditions).
Experimental designs have two very nice features. For one, they guarantee that the independent variable occurs prior to the measurement of the dependent variable. This eliminates the possibility of reverse causation. Second, the influence of common-causal variables is controlled, and thus eliminated, by creating initial equivalence among the participants in each of the experimental conditions before the manipulation occurs.
The most common method of creating equivalence among the experimental conditions is through random assignment to conditions, a procedure in which the condition that each participant is assigned to is determined through a random process, such as drawing numbers out of an envelope or using a random number table . Anderson and Dill first randomly assigned about 100 participants to each of their two groups (Group A and Group B). Because they used random assignment to conditions, they could be confident that, before the experimental manipulation occurred, the students in Group A were, on average, equivalent to the students in Group B on every possible variable, including variables that are likely to be related to aggression, such as parental discipline style, peer relationships, hormone levels, diet — and in fact everything else.
Then, after they had created initial equivalence, Anderson and Dill created the experimental manipulation — they had the participants in Group A play the violent game and the participants in Group B play the nonviolent game. Then they compared the dependent variable (the white noise blasts) between the two groups, finding that the students who had viewed the violent video game gave significantly longer noise blasts than did the students who had played the nonviolent game.
Anderson and Dill had from the outset created initial equivalence between the groups. This initial equivalence allowed them to observe differences in the white noise levels between the two groups after the experimental manipulation, leading to the conclusion that it was the independent variable (and not some other variable) that caused these differences. The idea is that the only thing that was different between the students in the two groups was the video game they had played.
Despite the advantage of determining causation, experiments do have limitations. One is that they are often conducted in laboratory situations rather than in the everyday lives of people. Therefore, we do not know whether results that we find in a laboratory setting will necessarily hold up in everyday life. Second, and more important, is that some of the most interesting and key social variables cannot be experimentally manipulated. If we want to study the influence of the size of a mob on the destructiveness of its behaviour, or to compare the personality characteristics of people who join suicide cults with those of people who do not join such cults, these relationships must be assessed using correlational designs, because it is simply not possible to experimentally manipulate these variables.
Key Takeaways
- Descriptive, correlational, and experimental research designs are used to collect and analyze data.
- Descriptive designs include case studies, surveys, and naturalistic observation. The goal of these designs is to get a picture of the current thoughts, feelings, or behaviours in a given group of people. Descriptive research is summarized using descriptive statistics.
- Correlational research designs measure two or more relevant variables and assess a relationship between or among them. The variables may be presented on a scatter plot to visually show the relationships. The Pearson Correlation Coefficient ( r ) is a measure of the strength of linear relationship between two variables.
- Common-causal variables may cause both the predictor and outcome variable in a correlational design, producing a spurious relationship. The possibility of common-causal variables makes it impossible to draw causal conclusions from correlational research designs.
- Experimental research involves the manipulation of an independent variable and the measurement of a dependent variable. Random assignment to conditions is normally used to create initial equivalence between the groups, allowing researchers to draw causal conclusions.
Exercises and Critical Thinking
- There is a negative correlation between the row that a student sits in in a large class (when the rows are numbered from front to back) and his or her final grade in the class. Do you think this represents a causal relationship or a spurious relationship, and why?
- Think of two variables (other than those mentioned in this book) that are likely to be correlated, but in which the correlation is probably spurious. What is the likely common-causal variable that is producing the relationship?
- Imagine a researcher wants to test the hypothesis that participating in psychotherapy will cause a decrease in reported anxiety. Describe the type of research design the investigator might use to draw this conclusion. What would be the independent and dependent variables in the research?
Image Attributions
Figure 3.4: “ Reading newspaper ” by Alaskan Dude (http://commons.wikimedia.org/wiki/File:Reading_newspaper.jpg) is licensed under CC BY 2.0
Aiken, L., & West, S. (1991). Multiple regression: Testing and interpreting interactions . Newbury Park, CA: Sage.
Ainsworth, M. S., Blehar, M. C., Waters, E., & Wall, S. (1978). Patterns of attachment: A psychological study of the strange situation . Hillsdale, NJ: Lawrence Erlbaum Associates.
Anderson, C. A., & Dill, K. E. (2000). Video games and aggressive thoughts, feelings, and behavior in the laboratory and in life. Journal of Personality and Social Psychology, 78 (4), 772–790.
Damasio, H., Grabowski, T., Frank, R., Galaburda, A. M., Damasio, A. R., Cacioppo, J. T., & Berntson, G. G. (2005). The return of Phineas Gage: Clues about the brain from the skull of a famous patient. In Social neuroscience: Key readings. (pp. 21–28). New York, NY: Psychology Press.
Freud, S. (1909/1964). Analysis of phobia in a five-year-old boy. In E. A. Southwell & M. Merbaum (Eds.), Personality: Readings in theory and research (pp. 3–32). Belmont, CA: Wadsworth. (Original work published 1909).
Kotowicz, Z. (2007). The strange case of Phineas Gage. History of the Human Sciences, 20 (1), 115–131.
Rokeach, M. (1964). The three Christs of Ypsilanti: A psychological study . New York, NY: Knopf.
Stangor, C. (2011). Research methods for the behavioural sciences (4th ed.). Mountain View, CA: Cengage.
Long Descriptions
Figure 3.6 long description: There are 25 families. 24 families have an income between $44,000 and $111,000 and one family has an income of $3,800,000. The mean income is $223,960 while the median income is $73,000. [Return to Figure 3.6]
Figure 3.10 long description: Types of scatter plots.
- Positive linear, r=positive .82. The plots on the graph form a rough line that runs from lower left to upper right.
- Negative linear, r=negative .70. The plots on the graph form a rough line that runs from upper left to lower right.
- Independent, r=0.00. The plots on the graph are spread out around the centre.
- Curvilinear, r=0.00. The plots of the graph form a rough line that goes up and then down like a hill.
- Curvilinear, r=0.00. The plots on the graph for a rough line that goes down and then up like a ditch.
[Return to Figure 3.10]
Introduction to Psychology - 1st Canadian Edition Copyright © 2014 by Jennifer Walinga and Charles Stangor is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.
Share This Book
- Research Process
- Manuscript Preparation
- Manuscript Review
- Publication Process
- Publication Recognition
- Language Editing Services
- Translation Services
Descriptive Research Design and Its Myriad Uses
- 3 minute read
Table of Contents
The design of a research study can be of two broad types—observational or interventional. In interventional studies, at least one variable can be controlled by the researcher. For example, drug trials that examine the efficacy of novel medicines are interventional studies. Observational studies, on the other hand, simply examine and describe uncontrollable variables¹ .
What is descriptive research design?¹
Descriptive design is one of the simplest forms of observational study design. It can either quantify the distribution of certain variables (quantitative descriptive research) or simply report the qualities of these variables without quantifying them (qualitative descriptive research).
When can descriptive research design be used?¹
It is useful when you wish to examine the occurrence of a phenomenon, delineate trends or patterns within the phenomenon, or describe the relationship between variables. As such, descriptive design is great for¹ :
- A survey conducted to measure the changes in the levels of customer satisfaction among shoppers in the US is the perfect example of quantitative descriptive research.
- Conversely, a case report detailing the experiences and perspectives of individuals living with a particular rare disease is a good example of qualitative descriptive research.
- Cross-sectional studies : Descriptive research is ideal for cross-sectional studies that capture a snapshot of a population at a specific point in time. This approach can be used to observe the variations in risk factors and diseases in a population. Take the following examples:
- In quantitative descriptive research: A study that measures the prevalence of heart disease among college students in the current academic year.
- In qualitative descriptive research: A cross-sectional study exploring the cultural perceptions of mental health across different communities.
- Ecological studies : Descriptive research design is also well-suited for studies that seek to understand relationships between variables and outcomes in specific populations. For example:
- A study that measures the relationship between the number of police personnel and homicides in India can use quantitative descriptive research design
- A study describing the impact of deforestation on indigenous communities’ cultural practices and beliefs can use qualitative descriptive research design.
- Focus group discussion reports : Descriptive research can help in capturing diverse perspectives and understanding the nuances of participants’ experiences.
- First, an example of quantitative descriptive research: A study that uses two focus groups to explore the perceptions of mental health among immigrants in London.
- Next, an example of qualitative descriptive research: A focus group report analyzing the themes and emotions associated with different advertising campaigns.
Benefits of descriptive research design¹
- Easy to conduct: Due to its simplicity, descriptive research design can be employed by researchers of all experience levels.
- Economical: Descriptive research design is not resource intensive. It is a budget-friendly approach to studying many phenomena without costly equipment.
- Provides comprehensive and useful information: Descriptive research is a more thorough approach that can capture many different aspects of a phenomena, facilitating a wholistic understanding.
- Aids planning of major projects or future research: As a tool for preliminary exploration, descriptive research guides can guide strategic decision-making and guide major projects.
The Bottom Line
Descriptive research plays a crucial role in improving our lives. Surveys help create better policies and cross-sectional studies help us understand problems affecting different populations including diseases. Used in the right context, descriptive research can advance knowledge and inform decision making¹ .
We, at Elsevier Language Services, understand the value of your descriptive research, as well as the importance of communicating it correctly. If you have a manuscript based on a descriptive study, our experienced editors can help improve its myriad aspects. By improving the logical flow, tone, and accuracy of your writing, we ensure that your descriptive research gets published in a top tier journal and makes maximum impact in academia and beyond. Contact us for a comprehensive list of services!
Type in wordcount for Plus Total: USD EUR JPY Follow this link if your manuscript is longer than 9,000 words. Upload
References
- Aggarwal, R., & Ranganathan, P. (2019). Study designs: Part 2 – Descriptive studies. Perspectives in Clinical Research , 10 (1), 34. https://doi.org/10.4103/picr.picr_154_18 .
Is The Use of AI in Manuscript Editing Feasible? Here’s Three Tips to Steer Clear of Potential Issues
Navigating “Chinglish” Errors in Academic English Writing
You may also like.
Five Common Mistakes to Avoid When Writing a Biomedical Research Paper
Making Technical Writing in Environmental Engineering Accessible
To Err is Not Human: The Dangers of AI-assisted Academic Writing
When Data Speak, Listen: Importance of Data Collection and Analysis Methods
Choosing the Right Research Methodology: A Guide for Researchers
Why is data validation important in research?
Writing a good review article
Scholarly Sources: What are They and Where can You Find Them?
Input your search keywords and press Enter.
Just one more step to your free trial.
.surveysparrow.com
Already using SurveySparrow? Login
By clicking on "Get Started", I agree to the Privacy Policy and Terms of Service .
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Enterprise Survey Software
Enterprise Survey Software to thrive in your business ecosystem
NPS® Software
Turn customers into promoters
Offline Survey
Real-time data collection, on the move. Go internet-independent.
360 Assessment
Conduct omnidirectional employee assessments. Increase productivity, grow together.
Reputation Management
Turn your existing customers into raving promoters by monitoring online reviews.
Ticket Management
Build loyalty and advocacy by delivering personalized support experiences that matter.
Chatbot for Website
Collect feedback smartly from your website visitors with the engaging Chatbot for website.
Swift, easy, secure. Scalable for your organization.
Executive Dashboard
Customer journey map, craft beautiful surveys, share surveys, gain rich insights, recurring surveys, white label surveys, embedded surveys, conversational forms, mobile-first surveys, audience management, smart surveys, video surveys, secure surveys, api, webhooks, integrations, survey themes, accept payments, custom workflows, all features, customer experience, employee experience, product experience, marketing experience, sales experience, hospitality & travel, market research, saas startup programs, wall of love, success stories, sparrowcast, nps® benchmarks, learning centre, testimonials, apps & integrations.
Our surveys come with superpowers ⚡
Blog General
Descriptive Research 101: Definition, Methods and Examples
Parvathi vijayamohan.
Last Updated:
16 July 2024
Table Of Contents
- Descriptive Research 101: The Definitive Guide
What is Descriptive Research?
- Key Characteristics
- Observation
- Case Studies
- Types of Descriptive Research
- Question Examples
- Real-World Examples
Tips to Excel at Descriptive Research
- More Interesting Reads
Imagine you are a detective called to a crime scene. Your job is to study the scene and report whatever you find: whether that’s the half-smoked cigarette on the table or the large “RACHE” written in blood on the wall. That, in a nutshell, is descriptive research .
Researchers often need to do descriptive research on a problem before they attempt to solve it. So in this guide, we’ll take you through:
- What is descriptive research + its characteristics
- Descriptive research methods
- Types of descriptive research
- Descriptive research examples
- Tips to excel at the descriptive method
Click to jump to the section that interests you.
Let’s begin by going through what descriptive studies can and cannot do.
Definition: As its name says, descriptive research describes the characteristics of the problem, phenomenon, situation, or group under study.
So the goal of all descriptive studies is to explore the background, details, and existing patterns in the problem to fully understand it. In other words, preliminary research.
However, descriptive research can be both preliminary and conclusive . You can use the data from a descriptive study to make reports and get insights for further planning.
What descriptive research isn’t: Descriptive research finds the what/when/where of a problem, not the why/how .
Because of this, we can’t use the descriptive method to explore cause-and-effect relationships where one variable (like a person’s job role) affects another variable (like their monthly income).
Key Characteristics of Descriptive Research
- Answers the “what,” “when,” and “where” of a research problem. For this reason, it is popularly used in market research , awareness surveys , and opinion polls .
- Sets the stage for a research problem. As an early part of the research process, descriptive studies help you dive deeper into the topic.
- Opens the door for further research. You can use descriptive data as the basis for more profound research, analysis and studies.
- Qualitative and quantitative research . It is possible to get a balanced mix of numerical responses and open-ended answers from the descriptive method.
- No control or interference with the variables . The researcher simply observes and reports on them. However, specific research software has filters that allow her to zoom in on one variable.
- Done in natural settings . You can get the best results from descriptive research by talking to people, surveying them, or observing them in a suitable environment. For example, suppose you are a website beta testing an app feature. In that case, descriptive research invites users to try the feature, tracking their behavior and then asking their opinions .
- Can be applied to many research methods and areas. Examples include healthcare, SaaS, psychology, political studies, education, and pop culture.
Descriptive Research Methods: The Top Three You Need to Know!
In short, survey research is a brief interview or conversation with a set of prepared questions about a topic. So you create a questionnaire, share it, and analyze the data you collect for further action.
Read more : The difference between surveys vs questionnaires
- Surveys can be hyper-local, regional, or global, depending on your objectives.
- Share surveys in-person, offline, via SMS, email, or QR codes – so many options!
- Easy to automate if you want to conduct many surveys over a period.
FYI: If you’re looking for the perfect tool to conduct descriptive research, SurveySparrow’s got you covered. Our AI-powered text and sentiment analysis help you instantly capture detailed insights for your studies.
With 1,000+ customizable (and free) survey templates , 20+ question types, and 1500+ integrations , SurveySparrow makes research super-easy.
Want to try out our platform? Click on the template below to start using it.👇
Product Market Research Survey Template
2. Observation
The observational method is a type of descriptive research in which you, the researcher, observe ongoing behavior.
Now, there are several (non-creepy) ways you can observe someone. In fact, observational research has three main approaches:
- Covert observation: In true spy fashion, the researcher mixes in with the group undetected or observes from a distance.
- Overt observation : The researcher identifies himself as a researcher – “The name’s Bond. J. Bond.” – and explains the purpose of the study.
- Participatory observation : The researcher participates in what he is observing to understand his topic better.
- Observation is one of the most accurate ways to get data on a subject’s behavior in a natural setting.
- You don’t need to rely on people’s willingness to share information.
- Observation is a universal method that can be applied to any area of research.
3. Case Studies
In the case study method, you do a detailed study of a specific group, person, or event over a period.
This brings us to a frequently asked question: “What’s the difference between case studies and longitudinal studies?”
A case study will go very in-depth into the subject with one-on-one interviews, observations, and archival research. They are also qualitative, though sometimes they will use numbers and stats.
An example of longitudinal research would be a study of the health of night shift employees vs. general shift employees over a decade. An example of a case study would involve in-depth interviews with Casey, an assistant director of nursing who’s handled the night shift at the hospital for ten years now.
- Due to the focus on a few people, case studies can give you a tremendous amount of information.
- Because of the time and effort involved, a case study engages both researchers and participants.
- Case studies are helpful for ethically investigating unusual, complex, or challenging subjects. An example would be a study of the habits of long-term cocaine users.
7 Types of Descriptive Research
Cross-sectional research | Studies a particular group of people or their sections at a given point in time. Example: current social attitudes of Gen Z in the US |
Longitudinal research | Studies a group of people over a long period of time. Example: tracking changes in social attitudes among Gen-Zers from 2022 – 2032. |
Normative research | Compares the results of a study against the existing norms. Example: comparing a verdict in a legal case against similar cases. |
Correlational/relational research | Investigates the type of relationship and patterns between 2 variables. Example: music genres and mental states. |
Comparative research | Compares 2 or more similar people, groups or conditions based on specific traits. Example: job roles of employees in similar positions from two different companies. |
Classification research | Arranges the data into classes according to certain criteria for better analysis. Example: the classification of newly discovered insects into species. |
Archival research | Searching for and extracting information from past records. Example: Tracking US Census data over the decades. |
Descriptive Research Question Examples
- How have teen social media habits changed in 10 years?
- What causes high employee turnover in tech?
- How do urban and rural diets differ in India?
- What are consumer preferences for electric vs. gasoline cars in Germany?
- How common is smartphone addiction among UK college students?
- What drives customer satisfaction in banking?
- How have adolescent mental health issues changed in 15 years?
- What leisure activities are popular among retirees in Japan?
- How do commute times vary in US metro areas?
- What makes e-commerce websites successful?
Descriptive Research: Real-World Examples To Build Your Next Study
1. case study: airbnb’s growth strategy.
In an excellent case study, Tam Al Saad, Principal Consultant, Strategy + Growth at Webprofits, deep dives into how Airbnb attracted and retained 150 million users .
“What Airbnb offers isn’t a cheap place to sleep when you’re on holiday; it’s the opportunity to experience your destination as a local would. It’s the chance to meet the locals, experience the markets, and find non-touristy places.
Sure, you can visit the Louvre, see Buckingham Palace, and climb the Empire State Building, but you can do it as if it were your hometown while staying in a place that has character and feels like a home.” – Tam al Saad, Principal Consultant, Strategy + Growth at Webprofits
2. Observation – Better Tech Experiences for the Elderly
We often think that our elders are so hopeless with technology. But we’re not getting any younger either, and tech is changing at a hair trigger! This article by Annemieke Hendricks shares a wonderful example where researchers compare the levels of technological familiarity between age groups and how that influences usage.
“It is generally assumed that older adults have difficulty using modern electronic devices, such as mobile telephones or computers. Because this age group is growing in most countries, changing products and processes to adapt to their needs is increasingly more important. “ – Annemieke Hendricks, Marketing Communication Specialist, Noldus
3. Surveys – Decoding Sleep with SurveySparrow
SRI International (formerly Stanford Research Institute) – an independent, non-profit research center – wanted to investigate the impact of stress on an adolescent’s sleep. To get those insights, two actions were essential: tracking sleep patterns through wearable devices and sending surveys at a pre-set time – the pre-sleep period.
“With SurveySparrow’s recurring surveys feature, SRI was able to share engaging surveys with their participants exactly at the time they wanted and at the frequency they preferred.”
Read more about this project : How SRI International decoded sleep patterns with SurveySparrow
1: Answer the six Ws –
- Who should we consider?
- What information do we need?
- When should we collect the information?
- Where should we collect the information?
- Why are we obtaining the information?
- Way to collect the information
#2: Introduce and explain your methodological approach
#3: Describe your methods of data collection and/or selection.
#4: Describe your methods of analysis.
#5: Explain the reasoning behind your choices.
#6: Collect data.
#7: Analyze the data. Use software to speed up the process and reduce overthinking and human error.
#8: Report your conclusions and how you drew the results.
Wrapping Up
Whether it’s social media habits, consumer preferences, or mental health trends, descriptive research provides a clear snapshot into what people actually think.
If you want to know more about feedback methodology, or research, check out some of our other articles below.
👉 Desk Research 101: Definition, Methods, and Examples
👉 Exploratory Research: Your Guide to Unraveling Insights
👉 Design Research: Types, Methods, and Importance
Growth Marketer at SurveySparrow
Fledgling growth marketer. Cloud watcher. Aunty to a naughty beagle.
You Might Also Like
17 product management kpis and metrics you need to know, employee health and safety: a guide to handling post-covid challenges, the best linktree alternatives for 2024, see it to believe it..
Please enter a valid Email ID.
14-Day Free Trial • Cancel Anytime • No Credit Card Required • Need a Demo?
Start your free trial today
No Credit Card Required. 14-Day Free Trial
Request a Demo
Want to learn more about SurveySparrow? We'll be in touch soon!
Scale up your descriptive research with the best survey software
Build surveys that actually work. give surveysparrow a free try today.
14-Day Free Trial • No Credit card required • 40% more completion rate
Hi there, we use cookies to offer you a better browsing experience and to analyze site traffic. By continuing to use our website, you consent to the use of these cookies. Learn More
Bridging the Gap: Overcome these 7 flaws in descriptive research design
Descriptive research design is a powerful tool used by scientists and researchers to gather information about a particular group or phenomenon. This type of research provides a detailed and accurate picture of the characteristics and behaviors of a particular population or subject. By observing and collecting data on a given topic, descriptive research helps researchers gain a deeper understanding of a specific issue and provides valuable insights that can inform future studies.
In this blog, we will explore the definition, characteristics, and common flaws in descriptive research design, and provide tips on how to avoid these pitfalls to produce high-quality results. Whether you are a seasoned researcher or a student just starting, understanding the fundamentals of descriptive research design is essential to conducting successful scientific studies.
Table of Contents
What Is Descriptive Research Design?
The descriptive research design involves observing and collecting data on a given topic without attempting to infer cause-and-effect relationships. The goal of descriptive research is to provide a comprehensive and accurate picture of the population or phenomenon being studied and to describe the relationships, patterns, and trends that exist within the data.
Descriptive research methods can include surveys, observational studies , and case studies, and the data collected can be qualitative or quantitative . The findings from descriptive research provide valuable insights and inform future research, but do not establish cause-and-effect relationships.
Importance of Descriptive Research in Scientific Studies
1. understanding of a population or phenomenon.
Descriptive research provides a comprehensive picture of the characteristics and behaviors of a particular population or phenomenon, allowing researchers to gain a deeper understanding of the topic.
2. Baseline Information
The information gathered through descriptive research can serve as a baseline for future research and provide a foundation for further studies.
3. Informative Data
Descriptive research can provide valuable information and insights into a particular topic, which can inform future research, policy decisions, and programs.
4. Sampling Validation
Descriptive research can be used to validate sampling methods and to help researchers determine the best approach for their study.
5. Cost Effective
Descriptive research is often less expensive and less time-consuming than other research methods , making it a cost-effective way to gather information about a particular population or phenomenon.
6. Easy to Replicate
Descriptive research is straightforward to replicate, making it a reliable way to gather and compare information from multiple sources.
Key Characteristics of Descriptive Research Design
The primary purpose of descriptive research is to describe the characteristics, behaviors, and attributes of a particular population or phenomenon.
2. Participants and Sampling
Descriptive research studies a particular population or sample that is representative of the larger population being studied. Furthermore, sampling methods can include convenience, stratified, or random sampling.
3. Data Collection Techniques
Descriptive research typically involves the collection of both qualitative and quantitative data through methods such as surveys, observational studies, case studies, or focus groups.
4. Data Analysis
Descriptive research data is analyzed to identify patterns, relationships, and trends within the data. Statistical techniques , such as frequency distributions and descriptive statistics, are commonly used to summarize and describe the data.
5. Focus on Description
Descriptive research is focused on describing and summarizing the characteristics of a particular population or phenomenon. It does not make causal inferences.
6. Non-Experimental
Descriptive research is non-experimental, meaning that the researcher does not manipulate variables or control conditions. The researcher simply observes and collects data on the population or phenomenon being studied.
When Can a Researcher Conduct Descriptive Research?
A researcher can conduct descriptive research in the following situations:
- To better understand a particular population or phenomenon
- To describe the relationships between variables
- To describe patterns and trends
- To validate sampling methods and determine the best approach for a study
- To compare data from multiple sources.
Types of Descriptive Research Design
1. survey research.
Surveys are a type of descriptive research that involves collecting data through self-administered or interviewer-administered questionnaires. Additionally, they can be administered in-person, by mail, or online, and can collect both qualitative and quantitative data.
2. Observational Research
Observational research involves observing and collecting data on a particular population or phenomenon without manipulating variables or controlling conditions. It can be conducted in naturalistic settings or controlled laboratory settings.
3. Case Study Research
Case study research is a type of descriptive research that focuses on a single individual, group, or event. It involves collecting detailed information on the subject through a variety of methods, including interviews, observations, and examination of documents.
4. Focus Group Research
Focus group research involves bringing together a small group of people to discuss a particular topic or product. Furthermore, the group is usually moderated by a researcher and the discussion is recorded for later analysis.
5. Ethnographic Research
Ethnographic research involves conducting detailed observations of a particular culture or community. It is often used to gain a deep understanding of the beliefs, behaviors, and practices of a particular group.
Advantages of Descriptive Research Design
1. provides a comprehensive understanding.
Descriptive research provides a comprehensive picture of the characteristics, behaviors, and attributes of a particular population or phenomenon, which can be useful in informing future research and policy decisions.
2. Non-invasive
Descriptive research is non-invasive and does not manipulate variables or control conditions, making it a suitable method for sensitive or ethical concerns.
3. Flexibility
Descriptive research allows for a wide range of data collection methods , including surveys, observational studies, case studies, and focus groups, making it a flexible and versatile research method.
4. Cost-effective
Descriptive research is often less expensive and less time-consuming than other research methods. Moreover, it gives a cost-effective option to many researchers.
5. Easy to Replicate
Descriptive research is easy to replicate, making it a reliable way to gather and compare information from multiple sources.
6. Informs Future Research
The insights gained from a descriptive research can inform future research and inform policy decisions and programs.
Disadvantages of Descriptive Research Design
1. limited scope.
Descriptive research only provides a snapshot of the current situation and cannot establish cause-and-effect relationships.
2. Dependence on Existing Data
Descriptive research relies on existing data, which may not always be comprehensive or accurate.
3. Lack of Control
Researchers have no control over the variables in descriptive research, which can limit the conclusions that can be drawn.
The researcher’s own biases and preconceptions can influence the interpretation of the data.
5. Lack of Generalizability
Descriptive research findings may not be applicable to other populations or situations.
6. Lack of Depth
Descriptive research provides a surface-level understanding of a phenomenon, rather than a deep understanding.
7. Time-consuming
Descriptive research often requires a large amount of data collection and analysis, which can be time-consuming and resource-intensive.
7 Ways to Avoid Common Flaws While Designing Descriptive Research
1. Clearly define the research question
A clearly defined research question is the foundation of any research study, and it is important to ensure that the question is both specific and relevant to the topic being studied.
2. Choose the appropriate research design
Choosing the appropriate research design for a study is crucial to the success of the study. Moreover, researchers should choose a design that best fits the research question and the type of data needed to answer it.
3. Select a representative sample
Selecting a representative sample is important to ensure that the findings of the study are generalizable to the population being studied. Researchers should use a sampling method that provides a random and representative sample of the population.
4. Use valid and reliable data collection methods
Using valid and reliable data collection methods is important to ensure that the data collected is accurate and can be used to answer the research question. Researchers should choose methods that are appropriate for the study and that can be administered consistently and systematically.
5. Minimize bias
Bias can significantly impact the validity and reliability of research findings. Furthermore, it is important to minimize bias in all aspects of the study, from the selection of participants to the analysis of data.
6. Ensure adequate sample size
An adequate sample size is important to ensure that the results of the study are statistically significant and can be generalized to the population being studied.
7. Use appropriate data analysis techniques
The appropriate data analysis technique depends on the type of data collected and the research question being asked. Researchers should choose techniques that are appropriate for the data and the question being asked.
Have you worked on descriptive research designs? How was your experience creating a descriptive design? What challenges did you face? Do write to us or leave a comment below and share your insights on descriptive research designs!
extremely very educative
Indeed very educative and useful. Well explained. Thank you
Simple,easy to understand
Excellent and easy to understand queries and questions get answered easily. Its rather clear than any confusion. Thanks a million Shritika Sirisilla.
Easy to understand. Well written , educative and informative
Rate this article Cancel Reply
Your email address will not be published.
Enago Academy's Most Popular Articles
- Industry News
Google Releases 2024 Scholar Metrics, Evaluates Impact of Scholarly Articles
Google has released its 2024 Scholar Metrics, assessing scholarly articles from 2019 to 2023. This…
Ensuring Academic Integrity and Transparency in Academic Research: A comprehensive checklist for researchers
Academic integrity is the foundation upon which the credibility and value of scientific findings are…
- Publishing Research
- Reporting Research
How to Optimize Your Research Process: A step-by-step guide
For researchers across disciplines, the path to uncovering novel findings and insights is often filled…
- Trending Now
Breaking Barriers: Sony and Nature unveil “Women in Technology Award”
Sony Group Corporation and the prestigious scientific journal Nature have collaborated to launch the inaugural…
Achieving Research Excellence: Checklist for good research practices
Academia is built on the foundation of trustworthy and high-quality research, supported by the pillars…
Choosing the Right Analytical Approach: Thematic analysis vs. content analysis for…
Comparing Cross Sectional and Longitudinal Studies: 5 steps for choosing the right…
Research Recommendations – Guiding policy-makers for evidence-based decision making
Sign-up to read more
Subscribe for free to get unrestricted access to all our resources on research writing and academic publishing including:
- 2000+ blog articles
- 50+ Webinars
- 10+ Expert podcasts
- 50+ Infographics
- 10+ Checklists
- Research Guides
We hate spam too. We promise to protect your privacy and never spam you.
- AI in Academia
- Promoting Research
- Career Corner
- Diversity and Inclusion
- Infographics
- Expert Video Library
- Other Resources
- Enago Learn
- Upcoming & On-Demand Webinars
- Peer-Review Week 2023
- Open Access Week 2023
- Conference Videos
- Enago Report
- Journal Finder
- Enago Plagiarism & AI Grammar Check
- Editing Services
- Publication Support Services
- Research Impact
- Translation Services
- Publication solutions
- AI-Based Solutions
- Thought Leadership
- Call for Articles
- Call for Speakers
- Author Training
- Edit Profile
I am looking for Editing/ Proofreading services for my manuscript Tentative date of next journal submission:
In your opinion, what is the most effective way to improve integrity in the peer review process?
Module 1: Introduction to Psychology & Psychology Research
Descriptive research, what you’ll learn to do: describe the strengths and weaknesses of descriptive, experimental, and correlational research.
If you think about the vast array of fields and topics covered in psychology, you understand that in order to do psychological research, there must be a diverse set of ways to gather data and perform experiments. For example, a biological psychologist might work predominately in a lab setting or alongside a neurologist. A social scientist may set up situational experiments, a health psychologist may administer surveys, and a developmental psychologist may make observations in a classroom. In this section, you’ll learn about the various types of research methods that psychologists employ to learn about human behavior.
Psychologists use descriptive, experimental, and correlational methods to conduct research. Descriptive, or qualitative, methods include the case study, naturalistic observation, surveys, archival research, longitudinal research, and cross-sectional research.
Experiments are conducted in order to determine cause-and-effect relationships. In ideal experimental design, the only difference between the experimental and control groups is whether participants are exposed to the experimental manipulation. Each group goes through all phases of the experiment, but each group will experience a different level of the independent variable: the experimental group is exposed to the experimental manipulation, and the control group is not exposed to the experimental manipulation. The researcher then measures the changes that are produced in the dependent variable in each group. Once data is collected from both groups, it is analyzed statistically to determine if there are meaningful differences between the groups.
When scientists passively observe and measure phenomena it is called correlational research. Here, psychologists do not intervene and change behavior, as they do in experiments. In correlational research, they identify patterns of relationships, but usually cannot infer what causes what. Importantly, with correlational research, you can examine only two variables at a time, no more and no less.
More on Research
If you enjoy learning through lectures and want an interesting and comprehensive summary of this section, then click on the link HERE (or on the link below) to watch a lecture given by MIT Professor John Gabrieli. Start at the 30:45 minute mark and watch through the end to hear examples of actual psychological studies and how they were analyzed. Listen for references to independent and dependent variables, experimenter bias, and double-blind studies. In the lecture, you’ll learn about breaking social norms, “WEIRD” research, why expectations matter, how a warm cup of coffee might make you nicer, why you should change your answer on a multiple choice test, and why praise for intelligence won’t make you any smarter.
Learning Objectives
- Differentiate between descriptive, experimental, and correlational research
- Explain the strengths and weaknesses of case studies, naturalistic observation, and surveys
- Describe the strength and weaknesses of archival research
- Compare longitudinal and cross-sectional approaches to research
There are many research methods available to psychologists in their efforts to understand, describe, and explain behavior and the cognitive and biological processes that underlie it. Some methods rely on observational techniques. Other approaches involve interactions between the researcher and the individuals who are being studied—ranging from a series of simple questions to extensive, in-depth interviews—to well-controlled experiments.
The three main categories of psychological research are descriptive, correlational, and experimental research. Research studies that do not test specific relationships between variables are called descriptive, or qualitative, studies . These studies are used to describe general or specific behaviors and attributes that are observed and measured. In the early stages of research it might be difficult to form a hypothesis, especially when there is not any existing literature in the area. In these situations designing an experiment would be premature, as the question of interest is not yet clearly defined as a hypothesis. Often a researcher will begin with a non-experimental approach, such as a descriptive study, to gather more information about the topic before designing an experiment or correlational study to address a specific hypothesis. Descriptive research is distinct from correlational research , in which psychologists formally test whether a relationship exists between two or more variables. Experimental research goes a step further beyond descriptive and correlational research and randomly assigns people to different conditions, using hypothesis testing to make inferences about how these conditions affect behavior. It aims to determine if one variable directly impacts and causes another. Correlational and experimental research both typically use hypothesis testing, whereas descriptive research does not.
Each of these research methods has unique strengths and weaknesses, and each method may only be appropriate for certain types of research questions. For example, studies that rely primarily on observation produce incredible amounts of information, but the ability to apply this information to the larger population is somewhat limited because of small sample sizes. Survey research, on the other hand, allows researchers to easily collect data from relatively large samples. While this allows for results to be generalized to the larger population more easily, the information that can be collected on any given survey is somewhat limited and subject to problems associated with any type of self-reported data. Some researchers conduct archival research by using existing records. While this can be a fairly inexpensive way to collect data that can provide insight into a number of research questions, researchers using this approach have no control on how or what kind of data was collected.
Correlational research can find a relationship between two variables, but the only way a researcher can claim that the relationship between the variables is cause and effect is to perform an experiment. In experimental research, which will be discussed later in the text, there is a tremendous amount of control over variables of interest. While this is a powerful approach, experiments are often conducted in very artificial settings. This calls into question the validity of experimental findings with regard to how they would apply in real-world settings. In addition, many of the questions that psychologists would like to answer cannot be pursued through experimental research because of ethical concerns.
The three main types of descriptive studies are case studies, naturalistic observation, and surveys.
Case Studies
In 2011, the New York Times published a feature story on Krista and Tatiana Hogan, Canadian twin girls. These particular twins are unique because Krista and Tatiana are conjoined twins, connected at the head. There is evidence that the two girls are connected in a part of the brain called the thalamus, which is a major sensory relay center. Most incoming sensory information is sent through the thalamus before reaching higher regions of the cerebral cortex for processing.
Link to Learning
To learn more about Krista and Tatiana, watch this New York Times video about their lives.
The implications of this potential connection mean that it might be possible for one twin to experience the sensations of the other twin. For instance, if Krista is watching a particularly funny television program, Tatiana might smile or laugh even if she is not watching the program. This particular possibility has piqued the interest of many neuroscientists who seek to understand how the brain uses sensory information.
These twins represent an enormous resource in the study of the brain, and since their condition is very rare, it is likely that as long as their family agrees, scientists will follow these girls very closely throughout their lives to gain as much information as possible (Dominus, 2011).
In observational research, scientists are conducting a clinical or case study when they focus on one person or just a few individuals. Indeed, some scientists spend their entire careers studying just 10–20 individuals. Why would they do this? Obviously, when they focus their attention on a very small number of people, they can gain a tremendous amount of insight into those cases. The richness of information that is collected in clinical or case studies is unmatched by any other single research method. This allows the researcher to have a very deep understanding of the individuals and the particular phenomenon being studied.
If clinical or case studies provide so much information, why are they not more frequent among researchers? As it turns out, the major benefit of this particular approach is also a weakness. As mentioned earlier, this approach is often used when studying individuals who are interesting to researchers because they have a rare characteristic. Therefore, the individuals who serve as the focus of case studies are not like most other people. If scientists ultimately want to explain all behavior, focusing attention on such a special group of people can make it difficult to generalize any observations to the larger population as a whole. Generalizing refers to the ability to apply the findings of a particular research project to larger segments of society. Again, case studies provide enormous amounts of information, but since the cases are so specific, the potential to apply what’s learned to the average person may be very limited.
Naturalistic Observation
If you want to understand how behavior occurs, one of the best ways to gain information is to simply observe the behavior in its natural context. However, people might change their behavior in unexpected ways if they know they are being observed. How do researchers obtain accurate information when people tend to hide their natural behavior? As an example, imagine that your professor asks everyone in your class to raise their hand if they always wash their hands after using the restroom. Chances are that almost everyone in the classroom will raise their hand, but do you think hand washing after every trip to the restroom is really that universal?
This is very similar to the phenomenon mentioned earlier in this chapter: many individuals do not feel comfortable answering a question honestly. But if we are committed to finding out the facts about hand washing, we have other options available to us.
Suppose we send a classmate into the restroom to actually watch whether everyone washes their hands after using the restroom. Will our observer blend into the restroom environment by wearing a white lab coat, sitting with a clipboard, and staring at the sinks? We want our researcher to be inconspicuous—perhaps standing at one of the sinks pretending to put in contact lenses while secretly recording the relevant information. This type of observational study is called naturalistic observation : observing behavior in its natural setting. To better understand peer exclusion, Suzanne Fanger collaborated with colleagues at the University of Texas to observe the behavior of preschool children on a playground. How did the observers remain inconspicuous over the duration of the study? They equipped a few of the children with wireless microphones (which the children quickly forgot about) and observed while taking notes from a distance. Also, the children in that particular preschool (a “laboratory preschool”) were accustomed to having observers on the playground (Fanger, Frankel, & Hazen, 2012).
Figure 1. Seeing a police car behind you would probably affect your driving behavior. (credit: Michael Gil)
It is critical that the observer be as unobtrusive and as inconspicuous as possible: when people know they are being watched, they are less likely to behave naturally. If you have any doubt about this, ask yourself how your driving behavior might differ in two situations: In the first situation, you are driving down a deserted highway during the middle of the day; in the second situation, you are being followed by a police car down the same deserted highway (Figure 1).
It should be pointed out that naturalistic observation is not limited to research involving humans. Indeed, some of the best-known examples of naturalistic observation involve researchers going into the field to observe various kinds of animals in their own environments. As with human studies, the researchers maintain their distance and avoid interfering with the animal subjects so as not to influence their natural behaviors. Scientists have used this technique to study social hierarchies and interactions among animals ranging from ground squirrels to gorillas. The information provided by these studies is invaluable in understanding how those animals organize socially and communicate with one another. The anthropologist Jane Goodall, for example, spent nearly five decades observing the behavior of chimpanzees in Africa (Figure 2). As an illustration of the types of concerns that a researcher might encounter in naturalistic observation, some scientists criticized Goodall for giving the chimps names instead of referring to them by numbers—using names was thought to undermine the emotional detachment required for the objectivity of the study (McKie, 2010).
Figure 2. (a) Jane Goodall made a career of conducting naturalistic observations of (b) chimpanzee behavior. (credit “Jane Goodall”: modification of work by Erik Hersman; “chimpanzee”: modification of work by “Afrika Force”/Flickr.com)
The greatest benefit of naturalistic observation is the validity, or accuracy, of information collected unobtrusively in a natural setting. Having individuals behave as they normally would in a given situation means that we have a higher degree of ecological validity, or realism, than we might achieve with other research approaches. Therefore, our ability to generalize the findings of the research to real-world situations is enhanced. If done correctly, we need not worry about people or animals modifying their behavior simply because they are being observed. Sometimes, people may assume that reality programs give us a glimpse into authentic human behavior. However, the principle of inconspicuous observation is violated as reality stars are followed by camera crews and are interviewed on camera for personal confessionals. Given that environment, we must doubt how natural and realistic their behaviors are.
The major downside of naturalistic observation is that they are often difficult to set up and control. In our restroom study, what if you stood in the restroom all day prepared to record people’s hand washing behavior and no one came in? Or, what if you have been closely observing a troop of gorillas for weeks only to find that they migrated to a new place while you were sleeping in your tent? The benefit of realistic data comes at a cost. As a researcher you have no control of when (or if) you have behavior to observe. In addition, this type of observational research often requires significant investments of time, money, and a good dose of luck.
Sometimes studies involve structured observation. In these cases, people are observed while engaging in set, specific tasks. An excellent example of structured observation comes from Strange Situation by Mary Ainsworth (you will read more about this in the chapter on lifespan development). The Strange Situation is a procedure used to evaluate attachment styles that exist between an infant and caregiver. In this scenario, caregivers bring their infants into a room filled with toys. The Strange Situation involves a number of phases, including a stranger coming into the room, the caregiver leaving the room, and the caregiver’s return to the room. The infant’s behavior is closely monitored at each phase, but it is the behavior of the infant upon being reunited with the caregiver that is most telling in terms of characterizing the infant’s attachment style with the caregiver.
Another potential problem in observational research is observer bias . Generally, people who act as observers are closely involved in the research project and may unconsciously skew their observations to fit their research goals or expectations. To protect against this type of bias, researchers should have clear criteria established for the types of behaviors recorded and how those behaviors should be classified. In addition, researchers often compare observations of the same event by multiple observers, in order to test inter-rater reliability : a measure of reliability that assesses the consistency of observations by different observers.
Often, psychologists develop surveys as a means of gathering data. Surveys are lists of questions to be answered by research participants, and can be delivered as paper-and-pencil questionnaires, administered electronically, or conducted verbally (Figure 3). Generally, the survey itself can be completed in a short time, and the ease of administering a survey makes it easy to collect data from a large number of people.
Surveys allow researchers to gather data from larger samples than may be afforded by other research methods . A sample is a subset of individuals selected from a population , which is the overall group of individuals that the researchers are interested in. Researchers study the sample and seek to generalize their findings to the population.
Figure 3. Surveys can be administered in a number of ways, including electronically administered research, like the survey shown here. (credit: Robert Nyman)
There is both strength and weakness of the survey in comparison to case studies. By using surveys, we can collect information from a larger sample of people. A larger sample is better able to reflect the actual diversity of the population, thus allowing better generalizability. Therefore, if our sample is sufficiently large and diverse, we can assume that the data we collect from the survey can be generalized to the larger population with more certainty than the information collected through a case study. However, given the greater number of people involved, we are not able to collect the same depth of information on each person that would be collected in a case study.
Another potential weakness of surveys is something we touched on earlier in this chapter: People don’t always give accurate responses. They may lie, misremember, or answer questions in a way that they think makes them look good. For example, people may report drinking less alcohol than is actually the case.
Any number of research questions can be answered through the use of surveys. One real-world example is the research conducted by Jenkins, Ruppel, Kizer, Yehl, and Griffin (2012) about the backlash against the US Arab-American community following the terrorist attacks of September 11, 2001. Jenkins and colleagues wanted to determine to what extent these negative attitudes toward Arab-Americans still existed nearly a decade after the attacks occurred. In one study, 140 research participants filled out a survey with 10 questions, including questions asking directly about the participant’s overt prejudicial attitudes toward people of various ethnicities. The survey also asked indirect questions about how likely the participant would be to interact with a person of a given ethnicity in a variety of settings (such as, “How likely do you think it is that you would introduce yourself to a person of Arab-American descent?”). The results of the research suggested that participants were unwilling to report prejudicial attitudes toward any ethnic group. However, there were significant differences between their pattern of responses to questions about social interaction with Arab-Americans compared to other ethnic groups: they indicated less willingness for social interaction with Arab-Americans compared to the other ethnic groups. This suggested that the participants harbored subtle forms of prejudice against Arab-Americans, despite their assertions that this was not the case (Jenkins et al., 2012).
Think It Over
A friend of yours is working part-time in a local pet store. Your friend has become increasingly interested in how dogs normally communicate and interact with each other, and is thinking of visiting a local veterinary clinic to see how dogs interact in the waiting room. After reading this section, do you think this is the best way to better understand such interactions? Do you have any suggestions that might result in more valid data?
Archival Research
Some researchers gain access to large amounts of data without interacting with a single research participant. Instead, they use existing records to answer various research questions. This type of research approach is known as archival research. Archival research relies on looking at past records or data sets to look for interesting patterns or relationships.
For example, a researcher might access the academic records of all individuals who enrolled in college within the past ten years and calculate how long it took them to complete their degrees, as well as course loads, grades, and extracurricular involvement. Archival research could provide important information about who is most likely to complete their education, and it could help identify important risk factors for struggling students (Figure 1).
Figure 1. A researcher doing archival research examines records, whether archived as a (a) hardcopy or (b) electronically. (credit “paper files”: modification of work by “Newtown graffiti”/Flickr; “computer”: modification of work by INPIVIC Family/Flickr)
In comparing archival research to other research methods, there are several important distinctions. For one, the researcher employing archival research never directly interacts with research participants. Therefore, the investment of time and money to collect data is considerably less with archival research. Additionally, researchers have no control over what information was originally collected. Therefore, research questions have to be tailored so they can be answered within the structure of the existing data sets. There is also no guarantee of consistency between the records from one source to another, which might make comparing and contrasting different data sets problematic.
Longitudinal and Cross-Sectional Research
Sometimes we want to see how people change over time, as in studies of human development and lifespan. When we test the same group of individuals repeatedly over an extended period of time, we are conducting longitudinal research. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time. For example, we may survey a group of individuals about their dietary habits at age 20, retest them a decade later at age 30, and then again at age 40.
Another approach is cross-sectional research. In cross-sectional research, a researcher compares multiple segments of the population at the same time. Using the dietary habits example above, the researcher might directly compare different groups of people by age. Instead a group of people for 20 years to see how their dietary habits changed from decade to decade, the researcher would study a group of 20-year-old individuals and compare them to a group of 30-year-old individuals and a group of 40-year-old individuals. While cross-sectional research requires a shorter-term investment, it is also limited by differences that exist between the different generations (or cohorts) that have nothing to do with age per se, but rather reflect the social and cultural experiences of different generations of individuals make them different from one another.
To illustrate this concept, consider the following survey findings. In recent years there has been significant growth in the popular support of same-sex marriage. Many studies on this topic break down survey participants into different age groups. In general, younger people are more supportive of same-sex marriage than are those who are older (Jones, 2013). Does this mean that as we age we become less open to the idea of same-sex marriage, or does this mean that older individuals have different perspectives because of the social climates in which they grew up? Longitudinal research is a powerful approach because the same individuals are involved in the research project over time, which means that the researchers need to be less concerned with differences among cohorts affecting the results of their study.
Often longitudinal studies are employed when researching various diseases in an effort to understand particular risk factors. Such studies often involve tens of thousands of individuals who are followed for several decades. Given the enormous number of people involved in these studies, researchers can feel confident that their findings can be generalized to the larger population. The Cancer Prevention Study-3 (CPS-3) is one of a series of longitudinal studies sponsored by the American Cancer Society aimed at determining predictive risk factors associated with cancer. When participants enter the study, they complete a survey about their lives and family histories, providing information on factors that might cause or prevent the development of cancer. Then every few years the participants receive additional surveys to complete. In the end, hundreds of thousands of participants will be tracked over 20 years to determine which of them develop cancer and which do not.
Clearly, this type of research is important and potentially very informative. For instance, earlier longitudinal studies sponsored by the American Cancer Society provided some of the first scientific demonstrations of the now well-established links between increased rates of cancer and smoking (American Cancer Society, n.d.) (Figure 2).
Figure 2. Longitudinal research like the CPS-3 help us to better understand how smoking is associated with cancer and other diseases. (credit: CDC/Debora Cartagena)
As with any research strategy, longitudinal research is not without limitations. For one, these studies require an incredible time investment by the researcher and research participants. Given that some longitudinal studies take years, if not decades, to complete, the results will not be known for a considerable period of time. In addition to the time demands, these studies also require a substantial financial investment. Many researchers are unable to commit the resources necessary to see a longitudinal project through to the end.
Research participants must also be willing to continue their participation for an extended period of time, and this can be problematic. People move, get married and take new names, get ill, and eventually die. Even without significant life changes, some people may simply choose to discontinue their participation in the project. As a result, the attrition rates, or reduction in the number of research participants due to dropouts, in longitudinal studies are quite high and increases over the course of a project. For this reason, researchers using this approach typically recruit many participants fully expecting that a substantial number will drop out before the end. As the study progresses, they continually check whether the sample still represents the larger population, and make adjustments as necessary.
- Introductory content. Provided by : Lumen Learning. License : CC BY-NC-SA: Attribution-NonCommercial-ShareAlike
- Modification, adaptation, and original content. Provided by : Lumen Learning. License : CC BY-SA: Attribution-ShareAlike
- Paragraph on correlation. Authored by : Christie Napa Scollon. Provided by : Singapore Management University. Located at : http://nobaproject.com/modules/research-designs?r=MTc0ODYsMjMzNjQ%3D . Project : The Noba Project. License : CC BY-NC-SA: Attribution-NonCommercial-ShareAlike
- Psychology, Approaches to Research. Authored by : OpenStax College. Located at : http://cnx.org/contents/[email protected]:mfArybye@7/Analyzing-Findings . License : CC BY: Attribution . License Terms : Download for free at http://cnx.org/contents/[email protected]
- Lec 2 | MIT 9.00SC Introduction to Psychology, Spring 2011. Authored by : John Gabrieli. Provided by : MIT OpenCourseWare. Located at : https://www.youtube.com/watch?v=syXplPKQb_o . License : CC BY-NC-SA: Attribution-NonCommercial-ShareAlike
- Descriptive Research. Provided by : Boundless. Located at : https://www.boundless.com/psychology/textbooks/boundless-psychology-textbook/researching-psychology-2/types-of-research-studies-27/descriptive-research-124-12659/ . License : CC BY-SA: Attribution-ShareAlike
- Researchers review documents. Authored by : National Cancer Institute. Provided by : Wikimedia. Located at : https://commons.wikimedia.org/wiki/File:Researchers_review_documents.jpg . License : Public Domain: No Known Copyright
Privacy Policy
How descriptive variable is handled or manipulated?
This is a question that comes up from time to time for our subject matter specialists. Today, we have the full, extensive explanation as well as the answer for everyone who is interested!
The answer is that in a descriptive study, the variables are not changed in any way, as we discovered earlier. They are observed in their natural state, and then the researchers study the relationships that exist between the variables.
In descriptive research, how is the handling or manipulation of variables performed?
In a descriptive study, there is no intentional manipulation of the variables, as we discovered earlier on… However, in descriptive research, variables are not described using the terms “independent” or “dependent.” While talking about the study, people usually refer to the variables by their actual names.
How is the variable that is being correlated handled or manipulated?
Again, the defining characteristic of correlational research is the absence of any manipulation of the variables being studied. It makes no difference where or how the variables are measured… Because there is no manipulation of an independent variable, both of these research can only be classified as correlational.
In what ways are the variables in the experiment managed or manipulated?
In most cases, an experiment will have three different variables: The variable that is under your control is known as the manipulated variable or the independent variable. The variable that you do not change at all is known as the controlled variable. What takes place as a direct consequence of the experiment is referred to as the responding variable or variables. This is also referred to as the output variable.
How are the variables that affect the evaluation managed or manipulated?
Researchers are interested in determining how changes in independent variables affect the dependent variables they are studying… The treatment or the intervention is the primary independent variable that is altered in an experiment. This is because the treatment or the intervention is what is being tested.
Controlled Variable and One That Is Manipulated
32 questions found in related categories
What exactly is an example of a manipulated variable?
In a scientific experiment, the one variable that the researcher intends to change is referred to as the “manipulated variable.” In the experiment involving salt and water, for instance, the variable that is being controlled is the amount of salt that is being added to the water. In the experiment with the plants, the variable that is being controlled is the amount of light.
How do you alter independent variables?
To reiterate, manipulating an independent variable involves systematically changing its level in such a way that either different groups of participants are exposed to varying levels of the variable over the course of the study, or the same group of participants is exposed to varying levels over the course of the study at different times.
What are 3 control variables?
In a standard scientific investigation, there are three categories of variables: controlled, independent, and dependent.
What is the correct usage of the term “manipulated variable” in a sentence?
Sentences Mobile
The PID control scheme gets its name from its three correcting terms; the total of these terms is what makes up the variable that is being managed. He did this by witnessing eggs hatching and changing elements critical to bird development, such as the birds’ calls. This allowed him to see the disparities in how birds develop.
In a scientific experiment, what aspect of the variable is changed?
The term “independent variables” (IV) refers to the aspects of a situation or set of circumstances that are subject to individual experimenter control. Your hypothesis is that this independent variable is directly affected by this other variable, which is the dependent variable.
Why do we choose to conduct our research using a correlational design?
All sort of study must begin with correlational research since it helps researchers to establish the statistical pattern between two variables that appear to be interconnected. As a result, correlational research serves as the foundation for all types of research. It enables you to relate 2 variables through the observation of their actions in the state in which they are the most natural.
What exactly does it mean to do research using a descriptive correlational method?
Studies that describe the variables and the relationships that arise naturally between and among them identify the studies as descriptive correlational studies. Designs for Predictive Correlational Analysis The variance of one or more variables can be predicted using predictive correlational research by analyzing the variance of one or more other variables.
What exactly is the point of using descriptive language?
The purpose of an investigation that is descriptive is to describe. It should not attempt to infer causal linkages between phenomena but rather present truthful, accurate, and systematic descriptions of those phenomena instead. It does not provide answers to inquiries regarding the how, when, or why a specific phenomena occurred.
Which variable represents the response will we get?
Response variables are outcomes that are going to be used as the primary proof of the therapeutic effect of the investigational medicine. These outcomes are defined as “response variables.” A treatment effect is an impact that is defined as one that is anticipated to result after the administration of a therapy.
What are the four primary formats for conducting research?
Quantitative research can be broken down into four primary categories: descriptive research, correlational research, causal-comparative/quasi-experimental research, and experimental research. attempts to determine the cause-and-effect correlations between the different factors. These kinds of designs are extremely analogous to actual trials, albeit with a few significant distinctions here and there.
What are some instances of manipulating others?
- Acting in a passive-aggressive manner.
- Implied or not spoken threats.
- Dishonesty.
- Keeping information secret from someone.
- separating a person from their loved ones and friends.
- Gaslighting.
- Verbal abuse.
- Make use of sexual activity in order to accomplish your objectives.
Which variable represents the constant?
TL;DR: In the context of a scientific experiment, a variable is said to be regulated or constant if it does not undergo any changes. For the purpose of conducting an experiment to determine the influence that different types of lighting have on plant growth and health, for instance, it would be necessary for other variables, such as the quality of the soil and the amount of watering, to remain same.
Does a manipulation of an independent variable need to take place?
The independent variable (IV) in a psychology experiment is the aspect of the study that is modified or manipulated by the researchers themselves and not by any of the other variables being tested in the study. The act of studying, for instance, would be considered the experiment’s independent variable if it were designed to examine how test scores are affected by the practice of studying.
Which two variables do you have influence over?
Examples of Factors That Can Be Controlled
The temperature is one example of a controlled variable that is frequently used. During an experiment, temperature can be considered controlled if it is maintained at a predetermined level. A controlled variable might also include the amount of light in the room, the type of glassware that was used, the level of humidity that was maintained, or the length of time that the experiment was conducted.
What are the five different categories of variables?
- Independent variables. An independent variable is a single property of your experiment that can’t be altered by any of the other variables in your experiment…
- Dependent variables. …
- Intervening variables. …
- Moderating variables. …
- Control variables. …
- Extraneous variables. …
- Quantitative variables. …
- Qualitative variables.
Is age a control variable?
Example: we are going to utilize age as the control variable; however, the relationship between the two variables is spurious and not genuine.) The gap between males and females disappears when age is held constant as a variable in the study.
How do we change the values of the variables?
When referring to an independent variable, what exactly are its levels.
The independent variable, which is the type of therapy, will have two levels if the experiment compares an experimental treatment to a control treatment; these levels are experimental and control, respectively. If there were going to be a comparison of five different diets in the experiment, then the independent variable, which would be diet, would have five different levels.
What are examples of quantitative variables?
As was covered in the portion of Chapter 1 devoted to variables, variables that are measured on a numeric scale are referred to as quantitative variables. Examples of quantitative variables are height, weight, reaction time, subjective pain rating, temperature, and test score. Other examples include temperature and subjective pain rating.
COMMENTS
Descriptive research aims to accurately and systematically describe a population, situation or phenomenon. It can answer what, where, when and how questions, but not why questions. A descriptive research design can use a wide variety of research methods to investigate one or more variables. Unlike in experimental research, the researcher does ...
Abstract One of the first steps in planning a research study is the choice of study design. The available study designs are divided broadly into two types - observational and interventional. Of the various observational study designs, the descriptive design is the simplest. It allows the researcher to study and describe the distribution of one or more variables, without regard to any causal ...
A manipulated variable is also sometimes called an independent variable. A response variable is the variable that changes as a result of the manipulated variable being changed. A response variable is sometimes called a dependent variable because its value often depends on the value of the manipulated variable.
Descriptive research aims is a type of research that provides an in-depth understanding of the study population, while correlational research is the type of research that measures the relationship between 2 variables.
Descriptive research design is employed across diverse fields, and its primary objective is to systematically observe and document all variables and conditions influencing the phenomenon. Read this comprehensive article to know what descriptive research is and the different methods, types and examples.
This descriptive research method involves observing and gathering data on a population or phenomena without manipulating variables. It is employed in psychology, market research, and other social science studies to track and understand human behavior. Observation is an essential component of descriptive research.
The research hypothesis suggests that the manipulated independent variable or variables will cause changes in the measured dependent variables. We can diagram the research hypothesis by using an arrow that points in one direction.
What is descriptive research design?¹ Descriptive design is one of the simplest forms of observational study design. It can either quantify the distribution of certain variables (quantitative descriptive research) or simply report the qualities of these variables without quantifying them (qualitative descriptive research).
Tourigny et al. (2011) used a non-experimental, quantitative research design known as a descriptive, comparative design. It is also known as casual comparative research and pre-experimental research. The basic purpose of these designs is to determine the relationship among variables.
Curious about descriptive research for your business? All you need to know descriptive research, methods, types and real-life examples.
Descriptive research may be an initial step before the other two types of psychological research are conducted: Correlational research: examines two variables at once, and may be used to identify ...
Descriptive research is non-experimental, meaning that the researcher does not manipulate variables or control conditions. The researcher simply observes and collects data on the population or phenomenon being studied.
A definition of a variable in terms of operations/activities that a research uses to measure/manipulate it Gives a variable a concrete definition so you can actually use it in an experiment, this allows the researcher to maintain consistency. All variables involved in a study should be operationalized Dependent Variables (what is measured) Independent Variables (what is manipulated) Defining ...
The three main categories of psychological research are descriptive, correlational, and experimental research. Research studies that do not test specific relationships between variables are called descriptive, or qualitative, studies. These studies are used to describe general or specific behaviors and attributes that are observed and measured.
How is the variable that is being correlated handled or manipulated? Again, the defining characteristic of correlational research is the absence of any manipulation of the variables being studied. It makes no difference where or how the variables are measured…
Variables are important to understand because they are the basic units of the information studied and interpreted in research studies. Researchers carefully analyze and interpret the value (s) of each variable to make sense of how things relate to each other in a descriptive study or what has happened in an experiment. previous next.
This short "snippet" covers three important aspects related to statistics - the concept of variables, the importance, and practical aspects related to descriptive statistics and issues related to sampling - types of sampling and sample size estimation. Keywords: Biostatistics, descriptive statistics, sample size, variables.
The research hypothesis suggests that the manipulated independent variable or variables will cause changes in the measured dependent variables. We can diagram the research hypothesis by using an arrow that points in one direction.
The goal of experimental research design is to provide more definitive conclusions about the causal relationships among the variables in the research hypothesis than is available from correlational designs. In an experimental research design, the variables of interest are called the independent variable (or variables) and the dependent variable.
Variables can be defined by the type of data (quantitative or categorical) and by the part of the experiment (independent or dependent).