quantitative research methods pros and cons

13 Pros and Cons of Quantitative Research Methods

Quantitative research utilizes mathematical, statistical, and computational tools to derive results. This structure creates a conclusiveness to the purposes being studied as it quantifies problems to understand how prevalent they are.

It is through this process that the research creates a projectable result which applies to the larger general population.

Instead of providing a subjective overview like qualitative research offers, quantitative research identifies structured cause-and-effect relationships. Once the problem is identified by those involved in the study, the factors associated with the issue become possible to identify as well. Experiments and surveys are the primary tools of this research method to create specific results, even when independent or interdependent factors are present.

These are the quantitative research pros and cons to consider.

List of the Pros of Quantitative Research

1. Data collection occurs rapidly with quantitative research. Because the data points of quantitative research involve surveys, experiments, and real-time gathering, there are few delays in the collection of materials to examine. That means the information under study can be analyzed very quickly when compared to other research methods. The need to separate systems or identify variables is not as prevalent with this option either.

2. The samples of quantitative research are randomized. Quantitative research uses a randomized process to collect information, preventing bias from entering into the data. This randomness creates an additional advantage in the fact that the information supplied through this research can then be statistically applied to the rest of the population group which is under study. Although there is the possibility that some demographics could be left out despite randomization to create errors when the research is applied to all, the results of this research type make it possible to glean relevant data in a fraction of the time that other methods require.

3. It offers reliable and repeatable information. Quantitative research validates itself by offering consistent results when the same data points are examined under randomized conditions. Although you may receive different percentages or slight variances in other results, repetitive information creates the foundation for certainty in future planning processes. Businesses can tailor their messages or programs based on these results to meet specific needs in their community. The statistics become a reliable resource which offer confidence to the decision-making process.

4. You can generalize your findings with quantitative research. The issue with other research types is that there is no generalization effect possible with the data points they gather. Quantitative information may offer an overview instead of specificity when looking at target groups, but that also makes it possible to identify core subjects, needs, or wants. Every finding developed through this method can go beyond the participant group to the overall demographic being looked at with this work. That makes it possible to identify trouble areas before difficulties have a chance to start.

5. The research is anonymous. Researchers often use quantitative data when looking at sensitive topics because of the anonymity involved. People are not required to identify themselves with specificity in the data collected. Even if surveys or interviews are distributed to each individual, their personal information does not make it to the form. This setup reduces the risk of false results because some research participants are ashamed or disturbed about the subject discussions which involve them.

6. You can perform the research remotely. Quantitative research does not require the participants to report to a specific location to collect the data. You can speak with individuals on the phone, conduct surveys online, or use other remote methods that allow for information to move from one party to the other. Although the number of questions you ask or their difficulty can influence how many people choose to participate, the only real cost factor to the participants involves their time. That can make this option a lot cheaper than other methods.

7. Information from a larger sample is used with quantitative research. Qualitative research must use small sample sizes because it requires in-depth data points to be collected by the researchers. This creates a time-consuming resource, reducing the number of people involved. The structure of quantitative research allows for broader studies to take place, which enables better accuracy when attempting to create generalizations about the subject matter involved. There are fewer variables which can skew the results too because you’re dealing with close-ended information instead of open-ended questions.

List of the Cons of Quantitative Research

1. You cannot follow-up on any answers in quantitative research. Quantitative research offers an important limit: you cannot go back to participants after they’ve filled out a survey if there are more questions to ask. There is a limited chance to probe the answers offered in the research, which creates fewer data points to examine when compared to other methods. There is still the advantage of anonymity, but if a survey offers inconclusive or questionable results, there is no way to verify the validity of the data. If enough participants turn in similar answers, it could skew the data in a way that does not apply to the general population.

2. The characteristics of the participants may not apply to the general population. There is always a risk that the research collected using the quantitative method may not apply to the general population. It is easy to draw false correlations because the information seems to come from random sources. Despite the efforts to prevent bias, the characteristics of any randomized sample are not guaranteed to apply to everyone. That means the only certainty offered using this method is that the data applies to those who choose to participate.

3. You cannot determine if answers are true or not. Researchers using the quantitative method must operate on the assumption that all the answers provided to them through surveys, testing, and experimentation are based on a foundation of truth. There are no face-to-face contacts with this method, which means interviewers or researchers are unable to gauge the truthfulness or authenticity of each result.

A 2011 study published by Psychology Today looked at how often people lie in their daily lives. Participants were asked to talk about the number of lies they told in the past 24 hours. 40% of the sample group reported telling a lie, with the median being 1.65 lies told per day. Over 22% of the lies were told by just 1% of the sample. What would happen if the random sampling came from this 1% group?

4. There is a cost factor to consider with quantitative research. All research involves cost. There’s no getting around this fact. When looking at the price of experiments and research within the quantitative method, a single result mist cost more than $100,000. Even conducting a focus group is costly, with just four groups of government or business participants requiring up to $60,000 for the work to be done. Most of the cost involves the target audiences you want to survey, what the objects happen to be, and if you can do the work online or over the phone.

5. You do not gain access to specific feedback details. Let’s say that you wanted to conduct quantitative research on a new toothpaste that you want to take to the market. This method allows you to explore a specific hypothesis (i.e., this toothpaste does a better job of cleaning teeth than this other product). You can use the statistics to create generalizations (i.e., 70% of people say this toothpaste cleans better, which means that is your potential customer base). What you don’t receive are specific feedback details that can help you refine the product. If no one likes the toothpaste because it tastes like how a skunk smells, that 70% who say it cleans better still won’t purchase the product.

6. It creates the potential for an unnatural environment. When carrying out quantitative research, the efforts are sometimes carried out in environments which are unnatural to the group. When this disadvantage occurs, the results will often differ when compared to what would be discovered with real-world examples. That means researchers can still manipulate the results, even with randomized participants, because of the work within an environment which is conducive to the answers which they want to receive through this method.

These quantitative research pros and cons take a look at the value of the information collected vs. its authenticity and cost to collect. It is cheaper than other research methods, but with its limitations, this option is not always the best choice to make when looking for specific data points before making a critical decision.

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20 Pros and Cons of Quantitative Research

The pros of quantitative research include swift data collection for rapid decision-making, reduced bias through randomized sampling, reliable forecasting from consistent findings, and broad market extrapolation from statistical analysis. These methods provide objective data that inform clear strategies and offer comprehensive market insights.

The cons of quantitative research involve limited qualitative feedback, potentially missing nuanced consumer insights, and a tendency to overlook long-term trends. Data-driven strategies may underrepresent participant experiences, and complex business motivations can be oversimplified. Additionally, the significant investment required for market research can be a drawback.

Quantitative Research Fact Sheet

• Nature of Quantitative Research : Expressed in numbers and graphs, allowing for visualization of data.
• Purpose : Utilized to test or confirm theories and assumptions, providing a basis for generalizations.
• Usage : Establishes generalizable facts about various subjects.
• Common Methods : Includes experiments, numerical observations, and surveys with closed-ended questions.
• Data Collection and Analysis : Involves collecting numerical data and employing statistical methods for analysis.
• Objective : Aims to produce objective, empirical data that is quantifiable.
• Sample Size : Data is often collected from large samples to enhance reliability and generalizability.
• Applications : Used to test hypotheses, identify patterns, and make predictions.
• Widely applied in psychology, economics, demography, sociology, marketing, community health, health & human development, gender studies, and political science.
• Can be repeated and reproduced due to standardized protocols and definitions, allowing for cross-cultural, temporal, or demographic comparisons.

Table of Contents

Pros of Quantitative Research

• Swift and Extensive Data Collection: Quantitative research methodologies, such as surveys and structured observations, facilitate the swift collection of vast amounts of data. For instance, utilizing online survey platforms enables researchers to reach thousands of participants across the globe in a matter of hours, expediting the research timeline significantly. This method proves invaluable in fields such as market research, where understanding consumer trends quickly can lead to significant competitive advantage.
• Minimization of Subjectivity and Bias: Quantitative research’s structured design, often involving random sampling and assignment, inherently guards against bias, thereby enhancing the credibility of the research findings. For example, in clinical trials, the use of a double-blind placebo-controlled design ensures that neither the subjects nor the researchers know who is receiving the treatment, which eliminates the risk of placebo effects or researcher-induced bias.
• Consistency and Replicability: The standardized approach of quantitative research, which includes replicable measures and observational techniques, ensures that studies can be repeated and verified. In the scientific community, this is paramount; for example, the consistent results across repeated trials of a new drug are what allow for its approval and widespread clinical use. Replicability also reinforces the strength of evidence when policies or decisions are based on research outcomes.
• Statistical Significance and Wider Applicability: Quantitative research results can be extrapolated to the broader population with statistical techniques, assuming the sample is representative. This is seen in national census data, where a stratified sample can provide insights into demographic changes and trends that inform policy decisions at the highest levels of government.
• Objective Data Analysis: The objective nature of quantitative research, with its emphasis on numbers and statistical analysis, limits the scope for researcher’s subjectivity. For example, in customer satisfaction research, using a Likert scale to quantify satisfaction levels allows for objective analysis of customer feedback, rather than relying on more subjective narrative responses.
• Comprehensive Population Insights: Quantitative studies can encompass broad aspects of population behaviors and characteristics, thereby providing a macro-level view of trends and patterns. For example, epidemiological studies examining the incidence of a disease across different regions and time periods rely on quantitative methods to track and predict health trends on a global scale.
• Generalizability of Findings: The structured nature of quantitative research often allows for findings to be generalized to larger groups beyond the sample when conditions are controlled. In educational research, standardized tests can provide data that, when analyzed, contribute to understanding educational outcomes across different populations and geographies.
• Clear, Focused Research Aims: The specificity with which quantitative research is designed ensures a clear and focused exploration of hypotheses. For instance, in economic research, specific variables such as interest rates or employment levels can be isolated and their impact on economic growth can be quantified and analyzed with precision.
• Enhanced Reliability Through Quantification: The use of statistical models and computational analysis enhances the reliability of quantitative research. For example, in finance, quantitative models are used to predict stock market trends, and the reliability of these models is continually tested against historical data and current market conditions.
• Identification and Analysis of Cause-and-Effect Relationships: Quantitative research is adept at identifying and rigorously testing cause-and-effect relationships. For instance, in social sciences, researchers can use statistical methods to determine the likelihood that a particular educational intervention causes improvements in student outcomes, controlling for other variables.

Cons of Quantitative Research

• Restricted Depth in Responses: Quantitative research typically doesn’t allow for probing or follow-up questions, which limits the depth of responses. For example, in a survey on job satisfaction, a participant may not have the opportunity to explain the unique factors influencing their satisfaction, potentially overlooking nuances that could be vital for organizational change.
• Potentially Artificial Settings: Conducting studies in controlled or unnatural settings can affect the behavior of participants, leading to outcomes that do not accurately reflect real-world scenarios. In market research, a focus group might react differently to a product in a testing facility than they would in their homes, which could skew the data about product usability.
• Risk of Oversimplification: The numerical focus of quantitative research may not capture the full scope of human experience, leading to an oversimplification of complex issues. For example, quantifying grief or happiness on a numeric scale can overlook the subjective intensity or personal significance of these emotions.
• Vulnerability to External Influences: Quantitative studies can be affected by external variables not accounted for in the research design, such as measurement errors or sampling biases. An educational assessment, for instance, could yield skewed results if the test environment is too noisy, potentially misrepresenting the students’ actual abilities.
• Intensive Resource Requirements: Gathering and analyzing quantitative data can be resource-heavy, demanding significant time, financial investment, and specialized expertise. In environmental studies, large-scale data collection efforts to monitor pollution levels can require costly equipment and numerous personnel to manage the data.
• Overemphasis on Numerical Data: There’s a risk in quantitative research of over-reliance on numbers, which may lead to neglecting important non-quantifiable factors. In employee performance metrics, focusing solely on sales figures might overlook critical elements such as customer service quality or team collaboration.
• Elevated Costs: The expenses associated with conducting comprehensive quantitative research, including materials and logistics, can be prohibitive. Large-scale health research often requires funding for medical equipment, staff, and the processing of numerous tests, which can amount to substantial sums.
• Artificial Research Conditions: The structured nature of quantitative research may create an artificial environment that does not authentically represent natural conditions. In behavioral studies, for example, participants might alter their natural responses due to the awareness of being observed or tested.
• Contextual Limitations: Quantitative data may fail to capture the full context of the research subject, possibly overlooking factors that influence the results. In social research, quantitative methods might not fully reflect the impact of cultural nuances on social behavior patterns.
• Inflexibility in Data Collection: The rigid structure of quantitative research instruments means there’s little room for adaptation once data collection has begun. If initial surveys in a consumer study don’t capture emerging trends, researchers can’t adjust questions mid-study to explore these new developments, potentially missing critical insights.

Type of Quantitative Data

Benefits of Rapid Data Collection

The efficiency of rapid data collection in quantitative research offers significant advantages for businesses, enabling them to respond quickly to market changes and make informed decisions. This speed and precision provide opportunities for immediate action, a clear advantage in today’s fast-paced commercial landscape.

One of the significant benefits of rapid data collection is the ability to seize opportunities as they arise. By quickly analyzing data, companies can spot market trends and patterns before their competitors do. This advantage gives them a head start in adjusting their strategies, launching new products, or targeting new market segments.

Quantitative research is also effective in spotting potential problems. If a product isn’t selling as expected or a marketing campaign isn’t getting the desired response, quick data collection allows businesses to identify the issue and implement corrections promptly.

Moreover, rapid data collection can improve customer service. By promptly gathering and analyzing customer feedback, companies can swiftly address any concerns or complaints, enhancing customer satisfaction and loyalty.

Importance of Randomized Sampling

Building on the benefits of rapid data collection, it’s crucial to consider how randomized sampling in quantitative research substantially enhances the quality and reliability of gathered data. The importance of randomized sampling can’t be overlooked when discussing the pros and cons of quantitative research.

• Reduction of bias : Researchers often favor randomized sampling as it minimizes selection bias, ensuring a fair representation of the population in the study.
• Enhanced reliability : Randomized sampling strengthens the reliability of obtained data, as it reduces the chance of systematic errors.
• Validity : By giving every member of a population an equal chance of being selected, randomized sampling enhances the validity of the research findings.
• Generalizability : This approach allows researchers to apply their findings to the broader population from which the sample was drawn, increasing the study’s generalizability.

The Role of Consistent Findings

In numerous business scenarios, consistent findings in quantitative research play a crucial role in underpinning reliable forecasting and strategic planning. These findings, derived from a multitude of data points, offer a solid foundation for making informed business decisions.

The role of consistent findings in quantitative research can’t be understated. Consistency provides a level of certainty, allowing businesses to predict trends, understand customer behavior, and develop effective strategies. However, it’s essential to consider the pros and cons of quantitative research. As beneficial as consistent findings are, they’re dependent on the accuracy and reliability of the data collected.

If the results are skewed or biased, the findings won’t provide an accurate reflection of the reality, which can lead to misguided strategies. This highlights another crucial role of consistent findings – they act as a check and balance system. They can identify anomalies or inconsistencies in the data that may indicate issues with collection or interpretation.

While the benefits of consistent findings in quantitative research are clear, they’re not without their drawbacks. Therefore, it’s important for businesses to understand and account for these potential pitfalls when leveraging quantitative research for strategic planning.

Drawbacks of Limited Qualitative Feedback

Despite the strengths of consistent findings, one potential pitfall of quantitative research lies in its limited capacity for qualitative feedback. This limitation can have a profound impact on research outcomes, rendering them less insightful than they might be with the inclusion of qualitative data.

• Missed nuances: The first disadvantage of limited qualitative feedback is the potential to miss nuanced elements of the data. Quantitative research thrives on numerical data, often overlooking the subtleties that qualitative research can highlight.
• Limited understanding of motivations: Without qualitative insights, quantitative research may not fully understand the motivations behind certain behaviors, leading to incomplete or even erroneous conclusions.
• Lack of context: Thirdly, the absence of qualitative feedback can leave data devoid of context, making it challenging to interpret results accurately.
• Reduced participant representation: Lastly, quantitative research can fail to represent individual participant experiences and perspectives, thereby limiting the depth of the research findings.

Issues With Snapshot Approach

Often, quantitative research’s snapshot approach doesn’t accurately reflect long-term market trends, causing potentially significant misinterpretations in business decision-making. This method, a common feature of quantitative research, collects data at a single point in time, providing a ‘snapshot’ of the market. While this approach is valuable for capturing immediate information, it often overlooks evolving trends and fluctuations, leading to a potential skew in market research.

One of the significant drawbacks of using quantitative research is this snapshot approach. It assumes that the market, consumer behaviors, and business operations remain static over time. This assumption is often incorrect as markets continuously evolve and change. Thus, the snapshot taken today may not be representative of the market’s state tomorrow, next week, or next month.

The snapshot approach’s limitations highlight the need for a balanced use of research methods. While quantitative research offers swift, generalizable results, it should be complemented with methods that capture ongoing changes. Using quantitative research over a more extended period, or combining it with qualitative methods, can yield a more comprehensive, accurate picture of the market, thereby informing more effective business strategies.

Impact of External Market Variables

Quantitative research, although robust, isn’t immune to external market variables that can skew data. Factors such as market fluctuations can impact the accuracy of findings, presenting challenges in data interpretation.

It’s essential, then, to investigate strategies for mitigating the effects of these variables to ensure sound research conclusions.

Data Skewness Risks

Market fluctuations present a significant risk to the accuracy of quantitative research data, potentially skewing results and leading to misleading conclusions. The impact of these external market variables reveals the limitations of quantitative research over qualitative. Notably, four significant risks arise:

• Inflation or Deflation : Rapid changes in the economy can distort projections, diluting the advantages of quantitative research.
• Market Volatility : Unpredictable shifts can invalidate data collected, diminishing reliability.
• Sudden Market Events : Unexpected occurrences like product recalls, scandals or natural disasters can radically alter consumer behavior, skewing data.
• Regulatory Changes : Governmental policy alterations can impact market trends, affecting data relevance.

These risks highlight the importance of considering market dynamics and external variables when conducting quantitative research.

Mitigating Variable Impact

Mitigating the impact of external market variables requires a strategic approach to quantitative research, ensuring that data remains relevant and accurate despite unpredictable market changes. Researchers must be vigilant, anticipating potential fluctuations and adjusting methodologies accordingly.

This can involve developing dynamic models that factor in variables like economic conditions, competitor activities, or technological advancements. By doing so, they can isolate and assess the impact of these factors on their data. This proactive approach reduces the risk of skewed results, enhancing the reliability of the research.

However, it’s not foolproof. The ever-changing nature of markets means some variables may still slip through, impacting data accuracy. Therefore, constant monitoring and adjustment are crucial to mitigating variable impact in quantitative research.

Frequently Asked Questions

What are some practical examples of quantitative research in business”.

Quantitative research’s practicality shines in business. It helps firms understand customer preferences through surveys, informs stock decisions with sales data analysis, and guides marketing strategies through social media metrics. It’s not perfect, but it’s invaluable.

How Does Quantitative Research Compare to Qualitative Research in Terms of Cost and Time Efficiency?”

Quantitative research typically costs more and takes longer than qualitative due to its scale. However, it’s often more time-efficient in the long run as it provides broad, generalizable results for strategic decision-making.

What Are Some Common Methodologies Used in Quantitative Research in Business?”

In business, common quantitative research methodologies include surveys, experiments, and observational studies. They’re chosen based on their ability to provide precise, objective data for decision-making and forecasting.

Can Quantitative Research Be Combined With Qualitative Methods for a More Holistic Market Analysis?”

Yes, they can combine quantitative research with qualitative methods for a more holistic market analysis. It’ll give them a more in-depth understanding of their market, enhancing the accuracy of their business decisions.

What Are Some Possible Solutions to the Disadvantages of Quantitative Research in Business?”

To counteract disadvantages of quantitative research in business, one could integrate qualitative methods, consider long-term trends, deepen consumer understanding, account for complex motivations, and adjust for market changes. This requires both resources and a nuanced approach.

Related Posts:

• Pros and Cons of Convenience Sampling
• Pros and Cons of Mixed Methods Research
• Pros and Cons of Statistical Analysis

Related posts:

• Pros and Cons of Market Research
• Pros and Cons of Narrative Research

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10 Advantages & Disadvantages of Quantitative Research

Quantitative research is a powerful tool for those looking to gather empirical data about their topic of study. Using statistical models and math, researchers evaluate their hypothesis.

Quantitative Research

When researchers look at gathering data, there are two types of testing methods they can use: quantitative research, or qualitative research. Quantitative research looks to capture real, measurable data in the form of numbers and figures; whereas qualitative research is concerned with recording opinion data, customer characteristics, and other non-numerical information.

Quantitative research is a powerful tool for those looking to gather empirical data about their topic of study. Using statistical models and math, researchers evaluate their hypothesis. An integral component of quantitative research - and truly, all research - is the careful and considered analysis of the resulting data points.

There are several key advantages and disadvantages to conducting quantitative research that should be considered when deciding which type of testing best fits the occasion.

5 Advantages of Quantitative Research

• Quantitative research is concerned with facts & verifiable information.

Quantitative research is primarily designed to capture numerical data - often for the purpose of studying a fact or phenomenon in their population. This kind of research activity is very helpful for producing data points when looking at a particular group - like a customer demographic. All of this helps us to better identify the key roots of certain customer behaviors. 

Businesses who research their customers intimately often outperform their competitors. Knowing the reasons why a customer makes a particular purchasing decision makes it easier for companies to address issues in their audiences. Data analysis of this kind can be used for a wide range of applications, even outside the world of commerce. 

• Quantitative research can be done anonymously. 

Unlike qualitative research questions - which often ask participants to divulge personal and sometimes sensitive information - quantitative research does not require participants to be named or identified. As long as those conducting the testing are able to independently verify that the participants fit the necessary profile for the test, then more identifying information is unnecessary. 

• Quantitative research processes don't need to be directly observed.

Whereas qualitative research demands close attention be paid to the process of data collection, quantitative research data can be collected passively. Surveys, polls, and other forms of asynchronous data collection generate data points over a defined period of time, freeing up researchers to focus on more important activities. 

• Quantitative research is faster than other methods.

Quantitative research can capture vast amounts of data far quicker than other research activities. The ability to work in real-time allows analysts to immediately begin incorporating new insights and changes into their work - dramatically reducing the turn-around time of their projects. Less delays and a larger sample size ensures you will have a far easier go of managing your data collection process.

• Quantitative research is verifiable and can be used to duplicate results.

The careful and exact way in which quantitative tests must be designed enables other researchers to duplicate the methodology. In order to verify the integrity of any experimental conclusion, others must be able to replicate the study on their own. Independently verifying data is how the scientific community creates precedent and establishes trust in their findings.

5 Disadvantages of Quantitative Research

• Limited to numbers and figures.

Quantitative research is an incredibly precise tool in the way that it only gathers cold hard figures. This double edged sword leaves the quantitative method unable to deal with questions that require specific feedback, and often lacks a human element. For questions like, “What sorts of emotions does our advertisement evoke in our test audiences?” or “Why do customers prefer our product over the competing brand?”, using the quantitative research method will not derive a meaningful answer.

• Testing models are more difficult to create.

Creating a quantitative research model requires careful attention to be paid to your design. From the hypothesis to the testing methods and the analysis that comes after, there are several moving parts that must be brought into alignment in order for your test to succeed. Even one unintentional error can invalidate your results, and send your team back to the drawing board to start all over again.

• Tests can be intentionally manipulative.  

Bad actors looking to push an agenda can sometimes create qualitative tests that are faulty, and designed to support a particular end result. Apolitical facts and figures can be turned political when given a limited context. You can imagine an example in which a politician devises a poll with answers that are designed to give him a favorable outcome - no matter what respondents pick.

• Results are open to subjective interpretation.

Whether due to researchers' bias or simple accident, research data can be manipulated in order to give a subjective result. When numbers are not given their full context, or were gathered in an incorrect or misleading way, the results that follow can not be correctly interpreted. Bias, opinion, and simple mistakes all work to inhibit the experimental process - and must be taken into account when designing your tests. 

• More expensive than other forms of testing. 

Quantitative research often seeks to gather large quantities of data points. While this is beneficial for the purposes of testing, the research does not come free. The grander the scope of your test and the more thorough you are in it’s methodology, the more likely it is that you will be spending a sizable portion of your marketing expenses on research alone. Polling and surveying, while affordable means of gathering quantitative data, can not always generate the kind of quality results a research project necessitates. 

Key Takeaways 

Numerical data is a vital component of almost any research project. Quantitative data can provide meaningful insight into qualitative concerns. Focusing on the facts and figures enables researchers to duplicate tests later on, and create their own data sets.

To streamline your quantitative research process:

Have a plan. Tackling your research project with a clear and focused strategy will allow you to better address any errors or hiccups that might otherwise inhibit your testing. 

Define your audience. Create a clear picture of your target audience before you design your test. Understanding who you want to test beforehand gives you the ability to choose which methodology is going to be the right fit for them. 

Test, test, and test again. Verifying your results through repeated and thorough testing builds confidence in your decision making. It’s not only smart research practice - it’s good business.

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Pros And Cons Of Qualitative Research vs Quantitative Research

Updated: Aug 16

In this post, you will learn the pros and cons of qualitative research vs quantitative research along with the differences and discover how both types of research can help and be applied to different business situations from ethnographic research to online surveys.

Table of contents:

The difference between qualitative and quantitative research

Pros and cons of qualitative research, pros and cons of quantitative research, so when can qualitative and quantitative research be applied, main types of qualitative research methods, key types of quantitative research methods.

The table above shows the advantages and disadvantages of using qualitative research and quantitative research.

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The main purpose of qualitative research is to explore the in-depth behaviour, opinions and attitudes of a small group of individuals in a more open manner instead of strictly following a set of questions. These tend to be face to face in-depth interviews or focus groups, where people can discuss the subject at hand openly with guidance from the interviewer.

While quantitative research is where results can be measured by numbers, which is easy to pick up and understand for those making the decisions . These quantified results are gathered by interviewing a large group of people (from 50 running into the 1000s) that is a reflection of the whole population you are targeting. Hence with a larger sample size, statistical analysis can be applied to provide better consumer insights such as predicted behaviour, best price levels and key drivers of buyers’ decisions.

Other than exploring attitudes and behaviour in detail, qualitative research is also used to test adverts, develop concepts and new products and build a picture of the market. Whereas quantitative research is used more for market measurements such as the number of people who use a product or service, awareness, consideration, preference, segmenting the market and how likely are they to buy.

Pros of qualitative research

Explores attitudes and behaviour in-depth.

Explores attitudes and behaviour in-depth as it’s more on a personal level and can delve in detail to gain a better understanding of their views and actions to generate or examine a hypothesis in more detail.

Encourages discussion

Encourages discussion as it’s more in an open manner instead of strictly following a fixed set of questions. In this way, it gives the research some context rather than just numbers.

Flexibility

Flexibility, where the interviewer can probe and is able to ask any questions around the subject matter, they feel is relevant or had not thought of before during the discussions and can even change the setting.

Cons of qualitative research

The sample size can be an issue.

The sample size can be an issue if you are taking the opinion of 5 people out of 300 of your customers or subscribers as a generalisation.

Bias in the sample selection

Bias in the sample selection, meaning the people you are selecting to take part in the qualitative research may all have a certain opinion of the subject matter rather than a group of people with mixed views, which is more valuable particularly if they are debating with opposing views during focus groups.

Lack of privacy

Lack of privacy, if you are covering sensitive topics then people taking part may not be comfortable in sharing their thoughts and opinions of the subject with others.

Whether you are using a skilled moderator or not

It is of vital importance; the moderator is skilled and experienced in managing the conversations of groups as well as being knowledgeable enough of the subject matter to ask relevant questions that may have not been thought of.

Pros of quantitative research

Larger sample sizes.

Larger sample sizes allowing for robust analysis of the results, so you are able to make more generalisations of your target audience.

Impartiality and accuracy of data

Impartiality and accuracy of the data as it based on the survey questions for screening, grouping and other hard number facts.

Faster and easier to run

Faster and easier to run particularly online and mobile surveys , where you can see the results in real time.

Data is anonymous

Data is anonymous especially with sensitive topics through self-completion exercises like online surveys.

Offers reliable and continuous information

Offers reliable and continuous information where you can repeat the survey again and again weekly, monthly, quarterly, yearly to gain consistent trend data to help you plan ahead or investigate and address issues.

Cons of quantitative research

Limited by the set answers on a survey.

Limited by the set answers on a survey, so you are unable to go beyond that in delving in more detail the behaviours, attitudes and reasons as you do with qualitative research. This is particularly true with self-completion surveys (online), where there is no interviewer probing you even if you include a couple of open-ended questions.

Research is not carried out in their normal environment

Research is not carried out in their normal environment, so can seem artificial and controlled. Answers given by participants are claimed and may not be their actual behaviour in real life.

Unable to follow-up any answers given following completion of survey

Unable to follow-up any answers given after they have completed the survey due to the anonymity of the participants. This is especially true for validity of the findings if the results are inconclusive. Although you can ask at the end of the survey if they would like to do a follow-up survey but not all participants may agree to do so.

Generally qualitative research is used for exploratory purposes to get a picture of what is going on or examining a hypothesis that can be tested later on. Although it can be used independently through a series of depth interviews and focus groups to explore concepts such as ideas for advertising or new products.

While with quantitative research you can gather measurable results that you can draw insights from and take action where needed like there is a drop in the number of visitors to your website page, which may be tackled through redesign of the webpage or promotions.

Read this post if you want run a survey - 5 Best Survey Maker Platforms To Consider Using

Qualitative and quantitative research is best utilised when they are combined and split into phases. For example, phase 1 could be exploratory research with qualitative research and then in phase 2 this is followed up with quantitative research to test the hypothesis that came up in the first phase. A post phase of qualitative research can be applied if there has been redesigns of the concept or to identify experiences after an event.

There are advantages in combining data and information from both methods where you can reap the benefits from the advantages that both methods have as well as countering the limitations through this hybrid approach. This is achieved through:

Enrichment by identifying issues not found in quantitative research

Examination via generating a hypothesis that can be tested.

Explanation through bringing the results to life by understanding any surprising results from the quantitative data.

Below are the most popular types of research within qualitative and quantitative research that you can use to achieve your objectives and answer questions you may have.

The three key tools of qualitative research are:

Focus groups – this is where a group of 5 to 10 people at a set location or on a private online forum discuss a topic of interest who have been pre-selected via screening to take part in. These group discussions are led by a person moderating the group.

Depth interviews – are one to one interviews that are either conducted face to face, over the phone or through video conferencing apps like Skype and Zoom. This allows the participant to talk at length in a more open manner and is especially good for sensitive topics. The interviewer will use a discussion guide to follow a relatively unstructured list of topics.

Ethnography and observation – are a fly on the wall way of listening and observing the behaviour of participants in certain real environments like shopping at a supermarket. Is great to capture the actual actions of participants rather than what they claim to do in a survey.

The 3 most popular methods of quantitative research:

Online surveys – is without a doubt the most popular type of research especially amongst consumer research as it’s quick, easy to do and relatively cheap compared to other methods. The great thing with online surveys is it easily accessible for everyone to take part in whether that’s on a laptop, mobile or tablet and can be on a website or survey links through social media and email. Plus, you can check out the results in real time.

If you are interested in creating a survey or poll you can try PickFu which is a easy to use interactive platform to set up surveys from scratch or have customisable templates to get you started with.

Telephone interviews – due to advancements in technology this is now used more for business to business research and interviews tend to last between 15 to 30 minutes. The advantage of this method is you have an interviewer who can probe or clarify any answers to open ended questions.

Face to face interviews – these are normally conducted in specific situations like shopping malls, exhibitions and the high street. As it’s more time consuming, costly and higher a security risk for interviewers, makes it the least popular method to use.

Social listening - is a form of secondary research where you can track, listen and respond to mentions about a brand or key topic on social media and elsewhere on the web. You can read more about it in this post - 3 Social Listening Tools To Consider

If you want to find out more how market research can help you, check out the posts below:

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18 Advantages and disadvantages of quantitative research

Quantitative research is a method of gathering and analyzing numerical data to understand a phenomenon or answer a research question.

It involves the use of quantitative data, which can be measured and analyzed using statistical techniques. In this article, we will explore the advantages and disadvantages of quantitative research.

Quantitative research is a method of empirical research that focuses on the systematic collection and analysis of numerical data. 

It is often used in social sciences, natural sciences, and various fields to gather and analyze data to make generalizations, identify patterns, and test hypotheses.

Here are some advantages and disadvantages of quantitative research:

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Advantages of Quantitative Research

• Objective and Reliable Data : Quantitative research method is based on numerical data, making it more objective and less susceptible to researcher bias compared to qualitative research methods.
• Generalizability : To use quantitative research often involves larger sample sizes, which can lead to more generalizable findings and results that can be applied to broader populations.
• Statistical Analysis : It allows for the use of statistical techniques to analyze data, providing a higher degree of precision and the ability to identify patterns and relationships in the data.
• Replicability : Because of its structured and standardized nature, quantitative research can be easily replicated by other researchers, increasing the reliability of findings.
• Quantifiable Outcomes : It is well-suited for measuring and quantifying variables, making it useful for assessing the impact of interventions or treatments.
• Efficiency : Data collection in quantitative method research can be efficient and less time-consuming, especially when using surveys or structured observations.
• Comparative Analysis : Researchers can compare variables, groups, or conditions to identify differences and associations, which can be useful for making informed decisions with data analysis.
• Objective Conclusions : The numerical data generated in quantitative research allows for clear and objective conclusions, facilitating decision-making and policy development.
• Numerical Representation : It provides data that can be graphically represented, making it easier for non-specialists to understand and interpret the findings.

Disadvantages of Quantitative Research

• Simplification : Quantitative research may oversimplify complex phenomena, as it often focuses on variables that can be easily measured, leaving out nuanced or qualitative aspects.
• Lack of Context : It may not capture the full context or meaning behind the data, as it typically does not explore the "why" and "how" of observed relationships.
• Limited Insight : Quantitative research may not provide in-depth insights into people's motivations, emotions, or experiences, which can be better explored through qualitative research methods.
• Difficulty in Capturing Unobservable Constructs : It may not effectively measure abstract or unobservable constructs, such as attitudes, beliefs, or cultural factors, which are better addressed through qualitative research.
• Risk of Measurement Error : Errors can occur during data collection or analysis, leading to inaccurate results. Researchers must take steps to minimize measurement error.
• Lack of Flexibility : Quantitative research typically follows a structured approach, which may limit the ability to adapt to unexpected findings or explore emergent themes.
• Resource-Intensive : Conducting quantitative research involves be resource-intensive, especially when large sample sizes are required or complex statistical analyses are involved.
• Ethical Concerns : The collection of quantitative data, particularly in surveys or experiments, may raise ethical concerns related to privacy of personal information, informed consent, and the potential for harm.
• Difficulty in Exploring Contextual Factors : Quantitative research may not fully capture the influence of contextual factors, such as culture, history, or environment, on the research topic.

Conclusion of Advantages and Disadvantages of Quantitative Research

Quantitative research is a powerful tool that allows researchers to collect and analyze numerical data to understand a phenomenon or answer research questions.

It offers several advantages, including objectivity, generalizability, real-time analysis, and the ability to analyze large datasets, different from the advantages and disadvantages of qualitative research .

However, it is important to recognize its limitations, such as the lack of qualitative richness, the need for a larger sample size, and the inability to explore complex social phenomena.

Researchers should carefully consider the advantages and disadvantages of quantitative research when selecting a research method for their study.

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Pros and Cons of Quantitative Research

Quantitative research allows you to measure and examine the data. In this type of research, you will understand the relationship between a dependent and independent variable. This is often used to test hypothesis in experiments, for statistical analysis, and for outsized scale surveys like census. Similar with other researchers, you need to know first how this quantitative research works. Before using this method, it is best to understand its pros and cons.

The Pros of Quantitative Research

Here are the main benefits of quantitative research:

• Objectivity: This type of research is numerical. Therefore, they can’t be easily misinterpreted. This allows you to investigate the same situation to know the investigation with the same quantitative method. You can also compare its results.

• Statistical Method: In quantitative research, you are giving a chance to use statistics. The forms of statistical data analysis permit you to understand a huge amount of essential characteristics of the data.

• Fast Data Collection: The data in quantitative research can be analyzed in a fast and easy way. With the use of statistically valid random models, a survey can immediately be generalized to the whole residents.

• Involves the Planning Method for Messages and Programs: With reliable details provided in the quantitative research, a trusted group of statistics can offer assurance when creating future plans.

The Cons of Quantitative Research

Here are the main disadvantages of quantitative research:

• Needs a Huge Sample of Population: In using this type of research, you need to find great numbers of correspondents. The larger the sample of people, the more statistically accurate the outputs will be. Therefore, you need to spend more time in finding these multiple correspondents.

• Requires Great Amount of Cash: When using this type of research, you have to ensure that you are financially prepared. Since you need a huge number of correspondents, you have to spend more cash for printing the questionnaire, transportation fees and a lot more. This is more costly compared to qualitative research.

How Do You Feel About Quantitative Research?

Using quantitative research also provides multiple benefits and few drawbacks. If you want to get the full benefits of this research, you need to know how it works. Before conducting a data, it is best to know your possible correspondents. You are also required to know how to interpret data and other related factors.

This quantitative research is best if you are planning to conduct a study about hypothesis and huge statistical examination. In case you are planning to have a small group of correspondent, it is best to use other methods. The best way to get a reliable result is by getting more correspondents. The more correspondents you have, the better statistics you will get.

For researches who desire to use this type of research, you need to be fully prepared. You need to know how to interview people, how to budget your money, how to manage your time, and a lot more. Depending on the scope of your research, it may take several months or years before you complete the study.

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• Qualitative vs. Quantitative Research | Differences, Examples & Methods

Qualitative vs. Quantitative Research | Differences, Examples & Methods

Published on April 12, 2019 by Raimo Streefkerk . Revised on June 22, 2023.

When collecting and analyzing data, quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings. Both are important for gaining different kinds of knowledge.

Common quantitative methods include experiments, observations recorded as numbers, and surveys with closed-ended questions.

Quantitative research is at risk for research biases including information bias , omitted variable bias , sampling bias , or selection bias . Qualitative research Qualitative research is expressed in words . It is used to understand concepts, thoughts or experiences. This type of research enables you to gather in-depth insights on topics that are not well understood.

Common qualitative methods include interviews with open-ended questions, observations described in words, and literature reviews that explore concepts and theories.

Table of contents

The differences between quantitative and qualitative research, data collection methods, when to use qualitative vs. quantitative research, how to analyze qualitative and quantitative data, other interesting articles, frequently asked questions about qualitative and quantitative research.

Quantitative and qualitative research use different research methods to collect and analyze data, and they allow you to answer different kinds of research questions.

Quantitative and qualitative data can be collected using various methods. It is important to use a data collection method that will help answer your research question(s).

Many data collection methods can be either qualitative or quantitative. For example, in surveys, observational studies or case studies , your data can be represented as numbers (e.g., using rating scales or counting frequencies) or as words (e.g., with open-ended questions or descriptions of what you observe).

However, some methods are more commonly used in one type or the other.

Quantitative data collection methods

• Surveys :  List of closed or multiple choice questions that is distributed to a sample (online, in person, or over the phone).
• Experiments : Situation in which different types of variables are controlled and manipulated to establish cause-and-effect relationships.
• Observations : Observing subjects in a natural environment where variables can’t be controlled.

Qualitative data collection methods

• Interviews : Asking open-ended questions verbally to respondents.
• Focus groups : Discussion among a group of people about a topic to gather opinions that can be used for further research.
• Ethnography : Participating in a community or organization for an extended period of time to closely observe culture and behavior.
• Literature review : Survey of published works by other authors.

A rule of thumb for deciding whether to use qualitative or quantitative data is:

• Use quantitative research if you want to confirm or test something (a theory or hypothesis )
• Use qualitative research if you want to understand something (concepts, thoughts, experiences)

For most research topics you can choose a qualitative, quantitative or mixed methods approach . Which type you choose depends on, among other things, whether you’re taking an inductive vs. deductive research approach ; your research question(s) ; whether you’re doing experimental , correlational , or descriptive research ; and practical considerations such as time, money, availability of data, and access to respondents.

Quantitative research approach

You survey 300 students at your university and ask them questions such as: “on a scale from 1-5, how satisfied are your with your professors?”

You can perform statistical analysis on the data and draw conclusions such as: “on average students rated their professors 4.4”.

Qualitative research approach

You conduct in-depth interviews with 15 students and ask them open-ended questions such as: “How satisfied are you with your studies?”, “What is the most positive aspect of your study program?” and “What can be done to improve the study program?”

Based on the answers you get you can ask follow-up questions to clarify things. You transcribe all interviews using transcription software and try to find commonalities and patterns.

Mixed methods approach

You conduct interviews to find out how satisfied students are with their studies. Through open-ended questions you learn things you never thought about before and gain new insights. Later, you use a survey to test these insights on a larger scale.

It’s also possible to start with a survey to find out the overall trends, followed by interviews to better understand the reasons behind the trends.

Qualitative or quantitative data by itself can’t prove or demonstrate anything, but has to be analyzed to show its meaning in relation to the research questions. The method of analysis differs for each type of data.

Analyzing quantitative data

Quantitative data is based on numbers. Simple math or more advanced statistical analysis is used to discover commonalities or patterns in the data. The results are often reported in graphs and tables.

Applications such as Excel, SPSS, or R can be used to calculate things like:

• Average scores ( means )
• The number of times a particular answer was given
• The correlation or causation between two or more variables
• The reliability and validity of the results

Analyzing qualitative data

Qualitative data is more difficult to analyze than quantitative data. It consists of text, images or videos instead of numbers.

Some common approaches to analyzing qualitative data include:

• Qualitative content analysis : Tracking the occurrence, position and meaning of words or phrases
• Thematic analysis : Closely examining the data to identify the main themes and patterns
• Discourse analysis : Studying how communication works in social contexts

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

• Chi square goodness of fit test
• Degrees of freedom
• Null hypothesis
• Discourse analysis
• Control groups
• Mixed methods research
• Non-probability sampling
• Quantitative research
• Inclusion and exclusion criteria

Research bias

• Rosenthal effect
• Implicit bias
• Cognitive bias
• Selection bias
• Negativity bias
• Status quo bias

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to systematically measure variables and test hypotheses . Qualitative methods allow you to explore concepts and experiences in more detail.

In mixed methods research , you use both qualitative and quantitative data collection and analysis methods to answer your research question .

The research methods you use depend on the type of data you need to answer your research question .

• If you want to measure something or test a hypothesis , use quantitative methods . If you want to explore ideas, thoughts and meanings, use qualitative methods .
• If you want to analyze a large amount of readily-available data, use secondary data. If you want data specific to your purposes with control over how it is generated, collect primary data.
• If you want to establish cause-and-effect relationships between variables , use experimental methods. If you want to understand the characteristics of a research subject, use descriptive methods.

Data collection is the systematic process by which observations or measurements are gathered in research. It is used in many different contexts by academics, governments, businesses, and other organizations.

There are various approaches to qualitative data analysis , but they all share five steps in common:

• Prepare and organize your data.
• Review and explore your data.
• Develop a data coding system.
• Assign codes to the data.
• Identify recurring themes.

The specifics of each step depend on the focus of the analysis. Some common approaches include textual analysis , thematic analysis , and discourse analysis .

A research project is an academic, scientific, or professional undertaking to answer a research question . Research projects can take many forms, such as qualitative or quantitative , descriptive , longitudinal , experimental , or correlational . What kind of research approach you choose will depend on your topic.

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12 Advantages and Disadvantages of Quantitative Research

The gathering of visible data to retort a research question utilizing mathematical, computational, or statistical methods is known as quantitative research, which, when compared to qualitative research, is much more valuable and accurate.

Information about numbers and quantities falls under quantitative research. This research utilizes mathematics, analytical methods, and statistical models for constructing and engaging unique concept philosophies or postulates.

Unlike qualitative actions, quantitative outcomes can be measured. The work takes a methodical approach and is based on an empirical study of measurable anomalies. This research produces a projectable outcome that extends to the broader population.

Unlike the subjective descriptions offered in qualitative research, quantitative research describes systematic relationships between cause and effect and if those involved in the study have identified the problem, it may be possible to identify the factors associated with the issue as well as the underlying causes of the problem.

Relationships that are numerical and measurable are looked at through quantitative research, which is widely utilized in proving the correctness of a hypothesis in marketing, sociology, and psychology. Quantitative research takes the first steps in finding the facts, instead of depending upon their instincts, and only then suggests the results of what is deemed to be the scientific method.

Pros and Cons of Quantitative Research

Irrespective of the research method, there are merits and demerits of any technique used and before utilizing quantitative research everyone should be aware of its benefits and its cons, some of which are presented below.

Advantages of Quantitative Research

A business, if it utilizes quantitative research, attains the following benefits

1. Company’s Self Esteem

Quantitative research comprises complex data analysis and statistics which, because of its difficulty in understanding the associated mathematics for most individuals, is believed to be impressive and priceless. This research technique, if utilized by any business, is highly reflective of its value and esteem.

2. Rapid Data Collection

The collection of data, in this case, using quantitative research methods is done in real-time to allow for the immediate occurrence of numerical scrutiny. With limited delays in resource attainment, correlations are found, which ultimately clues to a convenient deduction.

3. Randomized Models

Quantitative research utilizes randomized models for attaining data–which eliminates the appearance of favouritism in the majority of cases. Hence, this method grants the benefit of ensuring that the acquired information is available statistically to the remaining understudy populations.

4. Forthright Scrutiny

When collecting quantitative data, the results denote the suitability of the numerical tests to be performed, thus indicating the scrutiny required to be forthright and limiting the chances of subjectivity and error.

5. Repeatable and Trustworthy

The validity of the data from the quantitative study remains the same regardless of multiple examinations ensuring the repeatability of the attained facts. Additionally, the obtained info can end up being trustworthy, offering assurance throughout the decision-making process, and potentially even in the future.

6. Anonymous Research

Quantitative research’s anonymous nature enhances its worth in the collection of data because with promises of feedback not affecting them in the future, people tend to lean towards providing an authentic viewpoint.

Disadvantages of Quantitative Research

The use of quantitative research brings forth some of the following cons, and consideration of these cons is mandatory for leading effective research. Here are the cons:

1. Insecure Answers

Quantitative methods are mandated to operate assuming the results achieved from experiments and surveys are true since the presence of any face-to-face encounters using this approach is to no avail, which thus implies the insecurity of the answers’ truthfulness.

2. Peculiar Situation

Quantitative research can sometimes lead to results that are very different from those exposed in real-life samples because of the need to operate under circumstances unique to the group. This opens up the possibility for researchers to manipulate the outcomes regardless of the samples being randomized.

Consideration of quantitative research should not be made if one’s prime concern while conducting research is the price associated with it, since the procedure, and the outcome of this research comes at a price higher than expected.

4. No Follow-Up

One of the major limitations of quantitative research is that it doesn’t permit any follow-up to the answers presented by the participants. Once the survey is filled out by the participants, you are not permitted to return to them to answer your query.

5. Wrong Deduction

Regardless of the quantitative research being believed to be more scientific than qualitative research due to its association with the statistics, there may still be some factors leading the research to be misleading and subjective. The researchers’ biases and opinions are major factors in affecting the data collection of quantitative research.

6. Conclusion Not Specific to the Overall Populace

The use of randomized models isn’t guaranteed to be applicable to the overall populace and the risk of drawing a wrong deduction rises because of the use of random sources to acquire that information. Since not every individual takes part in the survey, the deduced outcomes can only be true of those who participate.

Finally, in most physical and biological disciplines, conducting quantitative analysis is unquestionably a necessary part of the process of determining the outcome of a given situation. This methodology is also contrasted with qualitative approaches, since it applies the same facts, but with different results.

Depending upon the suitability of the choice, either one of these research methods is used. The use of the quantitative method in the social sciences where personality is often more important than statistical data is more controversial.

The use of quantitative research is done to grant a detailed and measurable expression to the qualitative ideas, after which the conclusions drawn from the quantitative approach’s statistical analysis are understood using qualitative methods.

Thus, this is the reason for evaluating the quantitative analysis’s merits and demerits every time it becomes appropriate to collect data, which then aids us in concentrating on evidence rather than belief in ensuring its repeatability.

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