15 Advantages and Disadvantages of Quantitative Research

Quantitative research involves information that deals with quantities and numbers. That is different from the qualitative approach, which is known for observation and description. You can measure quantitative results, but you cannot do so for the qualitative work.

The research takes on a systematic approach that relies on an empirical investigation of observable phenomena. It uses statistical models, computational techniques, and mathematics to develop and employ hypotheses or theories regarding specific ideas. The process of measurement is central to the success of this work.

It is used widely in psychology, sociology, and marketing as a way to provide evidence that a hypothesis is correct. Instead of relying on instinct or opinion, this method of research seeks out facts before suggesting an outcome. That is why the research gets closely affiliated with the scientific method.

Several advantages and disadvantages of quantitative research are worth reviewing when there is a hypothesis under consideration.

List of the Advantages of Quantitative Research

1. The quantitative approach allows you to reach a higher sample size.
When you have the ability to study a larger sample size for any hypothesis, then it is easier to reach an accurate generalized conclusion. The additional data that you receive from this work gives the outcome greater credibility because the statistical analysis has more depth to review. A larger sample makes it less likely that outliers in the study group can adversely impact the results you want to achieve impartially.

2. You can collect information quickly when using quantitative research.
Researchers collect information for the quantitative research process in real-time scenarios so that statistical analysis can occur almost immediately. Experiments, surveys, and interviews provide immediate answers that become useful from a data-centered approach. Fewer delays in the acquisition of these resources makes it easier to find correlations that eventually lead toward a useful conclusion.

Quantitative research doesn’t require the separation of systems or the identification of variables to produce results. That’s why it is a straightforward process to implement.

3. Quantitative research uses randomized samples.
When research participants suspect that a study wants to achieve a specific result, then their personal bias can enter into the data spectrum. The answers provided on the included materials are partial truths or outright lies as a way to manipulate the work. That’s why the quantitative approach is so useful when trying to study a specific hypothesis within a large population demographic.

This approach uses a randomized process to collect information. That excludes bias from appearing in most situations. It also provides an advantage in the fact that the data can then get statistically applied to the rest of the demographic being studied. There is always a risk of error to consider, but it is this method that typically supplies the most factual results.

4. Results duplication is possible when using quantitative research.
When opinions are a valid substitute for facts, then anything becomes possible. Quantitative research eliminates this problem because it only focuses on actual data. The work validates itself because the results always point toward the same data, even though randomized conditions exist. There can be minute variations found over time, but the general conclusions that researchers develop when using this process stay accurate.

That’s why this information is useful when looking at the need for specific future outcomes. The facts provide statistics that are suitable to consider when difficult decisions must get made.

5. Quantitative research can focus on facts or a series of information.
Researchers can use the quantitative approach to focus on a specific fact that they want to study in the general population. This method is also useful when a series of data points are highly desirable within a particular demographic. It is a process that lets us understand the reasons behind our decisions, behaviors, or actions from a societal viewpoint.

When we can comprehend the meaning behind the decisions that people make, then it is easier to discover pain points or specific preferences that require resolution. Then the data analysis can extend to the rest of the population so that everyone can benefit from this work.

6. The research performed with the quantitative approach is anonymous.
As long as researchers can verify that individuals fit in the demographic profile of their study group, there is no need to provide personal information. The anonymous nature of quantitative research makes it useful for data collection because people are more likely to share an honest perspective when there are guarantees that their feedback won’t come back to haunt them. Even when interviews or surveys are part of this work, the personal information is a screening tool instead of an identifying trademark.

7. Quantitative research doesn’t require direct observation to be useful.
Researchers must follow specific protocols when using the quantitative method, but there isn’t a requirement to directly observe each participant. That means a study can send surveys to individuals without the need to have someone in the room while they provide answers. This advantage creates a better response rate because people have more time and less pressure to complete the work.

Although the difficulty of the questions asked or the length of a survey or interview can be barriers to participation, the amount of data that researchers collect from the quantitative process is always useful.

List of the Disadvantages of Quantitative Research

1. This method doesn’t consider the meaning behind social phenomena.
The quantitative approach wants to find answers to specific questions so that a particular hypothesis can be proven or disproven. It doesn’t care about the motives that people have when sharing an opinion or making a decision. The goal of this information collecting process is to paint a present-time picture of what is happening in the selected demographic. That means this option cannot measure the ways in which society changes or how people interpret their actions or that of others.

2. Every answer provided in this research method must stand on its own.
Quantitative research does not give you the option to review answers with participants. The replies provided to researchers must stand by themselves, even if the information seems confusing or it is invalid. Instead of following a tangent like other methods use, the quantitative option has very few opportunities to ask for clarity.

Part of this disadvantage is due to the anonymous nature of the data that researchers collect. If an answer provides inconclusive results, then there is no way to guarantee the validity of what was received. It is even possible to skew results when a question might be incorrectly formatted.

3. Quantitative research sometimes creates unnatural environments.
Quantitative research works well when a verifiable environment is available for study. Researchers can then take advantage of the decisions made in that arena to extrapolate data that is useful for review. There can be times when this approach generates an unnatural scenario based on the questions asked or the approaches used to solicit information. Just as a participant can attempt to skew results by providing falsified answers, researchers can attempt the same result by influencing the design of the work in its initial stages.

4. Some efforts at randomization will not create usable information.
The quantitative approach doesn’t look for the reason why variables exist in specific environments. Its goal is to find the different aspects of a demographic in a particular setting to extrapolate data that can be used for generalization purposes. Although the impact of randomization adds validity to the final result, there can be times when the information isn’t usable.

One person might decide to purchase pizza because they’ve had a long day at work and don’t feel like cooking at home. Another individual could make the same decision because it’s Tuesday, and they always purchase pizza on that day. A third household might become customers of a pizzeria because they are celebrating a family birthday. Quantitative data looks at the fact that everyone bought pizza, and it doesn’t care about the reasons why.

5. There is no access to specific feedback.
Quantitative research could be best described as a pass-fail grade. You know for certain that a majority of a population demographic will feel a specific way about a particular situation because of the data that researchers collect. You know that everyone purchases pizza, but what you don’t know is how many people enjoyed the experience and will come back for another transaction in the future.

The statistics that researchers gather when using this approach are useful for generalizations that let you see if goods or services earn a passing grade in a specific demographic. What this data cannot produce are specific feedback incidents that allow for positive refinement.

6. Quantitative research studies can be very expensive.
If the price is an issue when research work must be done, then the quantitative approach has a significant barrier to consider. A single result may cost more than $100,000 when corporate interests are seeking more data to analyze. One of the most popular methods when using this approach is to use a focus group. Working with groups of participants to solicit answers is about 40% cheaper than other information collection methods, but it is still a problematic approach for small businesses to manage.

There are some affordable methods to use when considering the quantitative research method, such as online polling or emails, but you don’t have any guarantees that the respondents fit into your targeted demographic.

7. Answer validity always creates a cloud of doubt on the final results.
Researchers have no meaningful way to determine if the answers someone gives during a quantitative research effort are accurate. This work always gets based on the assumption that everyone is honest and each situation. Since direct observation isn’t always possible with this approach, the data always has a tinge of doubt to it, even when generalizing the results to the rest of the population.

This disadvantage is the reason why you see so many duplicated quantitative research efforts. When the same results occur multiple times, then there is more confidence in the data produced. If different outcomes happen, then researchers know that there are information concerns that require management.

8. Individual characteristics don’t always apply to the general population.
Researchers are always facing the risk that the answers or characteristics given in a quantitative study aren’t an accurate representation of the entire population. It is relatively easy to come to false conclusions or correlations because of the assumptions that are necessary for this work. Even the randomized sampling that takes place to remove bias from the equation isn’t 100% accurate. The only certainty that we have from this data is that if we gather enough of it, then the averages that come out of the data analysis offer a path toward something usable.

Conclusion

The use of quantitative research is uncontroversial in most biological and physical sciences. It often gets compared with qualitative methods because the same truth applies to that approach. Each one gets used when it is the most appropriate option.

It is more controversial to use the quantitative method in the social sciences where individuality is sometimes more important than demographical data.

We use quantitative methods to provide testable and precise expressions to qualitative ideas. Then we use the qualitative methods to understand the conclusions that we generate from the statistical analysis of the quantitative approach.

That’s why we review the advantages and disadvantages of quantitative research whenever data collection is necessary. It allows us to focus on facts instead of opinion in a way that we can duplicate in future studies.

About the Author of this Blog Post
Natalie Regoli, Esq. is the author of this post and the editor-in-chief of our blog. She received her B.A. in Economics from the University of Washington and her Masters in Law from The University of Texas School of Law. In addition to being a seasoned writer, Natalie has almost two decades of experience as a lawyer and banker. If you would like to reach out to contact Natalie, then go here to send her a message.