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Types of quantitative research

You need quantitative research data, conducted on a statistically significant sample to get the most informative results for your business.

You may already use quantitative research, or you may be new to this research type. Join us as we explore quantitative research, how to use it, and the best ways to collect quantitative data.

Research in which collected data is converted into numbers or numerical data is quantitative research. It is widely used in surveys, demographic studies, census information, marketing, and other studies that use numerical data to analyze results. 

Primary quantitative research yields results that are objective, statistical, and unbiased. These results are often used as benchmarks. 

Distinguishing features of quantitative research:

  • Data is numerical
  • Analysis is from a statistical perspective
  • Conducted on a statistically significant sample size that is representative of the target market
  • Uses structured tools, such as surveys, to gather data
  • Uses closed-ended questions focused on the end goal of the research
  • Can provide generalized results that represent an entire population
  • Can be used to find patterns and averages
  • Can be used to make predictions
  • Can test causal relationships

As we just described, quantitative research collects numerical data. It is statistical and structured, and its results are objective and conclusive.

Qualitative research collects non-numerical data to gain insights. It is performed with the goal of gaining a deeper understanding of a topic, issue, or problem from an individual perspective. Data is meant to describe rather than predict. Information is gathered through focus groups, observation, and open-ended survey questions.

Qualitative research data is not numerical. Because of its exploratory nature, answers are descriptive text or statements rather than choices from a structured answer set. This makes qualitative research more time-consuming to analyze than quantitative research, though it is equally valuable in a well-structured survey.

Refer to this article for further information about the difference between quantitative and qualitative research.

There are several advantages to quantitative research. Some of the most salient advantages are:

  • Reliable data: data collected in quantitative research is reliable and accurate because it is collected, analyzed, and presented in numerical form. 
  • Study can be replicated: standardized collection allows the study to be performed again to directly compare results.
  • Fast and easy collection of data: quantitative research data can be collected quickly and the process of conducting a survey with the quantitative research method is straightforward and less time-consuming than qualitative research.
  • Wider scope of data analysis: quantitative research provides a wider scope of analysis with the use of statistics.
  • Eliminates bias: there is no scope for personal opinions or biasing of results in the numerical data. 
  • Less interpretation of results: accept or reject your hypothesis based on numerical data.

No research method is perfect. These are some of the main limitations of quantitative research:

  • Superficial representation: complex concepts such as feelings and opinions cannot be expressed
  • Data can be over-manipulated: missing data, imprecise measurements, or inappropriate sampling are biases that can lead to inaccurate conclusions
  • Difficult to analyze without a tool: statistical analysis can be challenging to perform without statistics knowledge and experience or a tool that performs statistical analysis

Quantitative research methods are used for descriptive, correlational, causal-comparative, and experimental research. Let’s take a closer look at each type.

This type of quantitative research is used to explain the current state of a variable or topic. It can answer what, where, when, and how, but not why questions (those are answered in qualitative research). The researcher does not control or manipulate the variables. They just observe and measure them.

Surveys are often used to gather a large amount of data that can be analyzed for frequencies, averages, and patterns. For example, surveys can be used to describe the demographics of a given region, gauge public opinion on political topics, and evaluate customer satisfaction with a company’s products.

Observations are often used to gather data without relying on survey respondents' honesty or accuracy. This method of descriptive research is used to understand how individuals act in real-life situations.

Case studies can also be used to gather detailed information to identify characteristics of a narrowly defined subject. They are frequently used to generate hypotheses and theories.


The goal of descriptive research is to understand the current status of an identified variable. 

When to Use

Descriptive research is used to identify categories and trends, form hypotheses, arrange comparisons, confirm existing phenomena, and outline sample characteristics.

The following are examples of descriptive research:

  • An athletic shoe brand conducts a demographic survey to understand the shoe purchasing trends among customers in New York.
  • Find out where young adults aged 16-20 get their online news with a survey listing popular news sites.
  • Discover how often working people take vacations by sending surveys asking how many vacations the target population has taken in the last year.

The correlational research method examines the relationships between different subjects and variables without the researcher controlling or manipulating any of them. It is focused on relationships between fixed variables. Correlational research relies on the scientific method and hypotheses.

Surveys are fast, easy ways to measure your variables of interest. It’s essential to ensure that your questions are formulated correctly and your questions are free of bias. Our question bank is very useful in helping you design your survey questions.

Naturalistic observation allows you to gather data about a behavior or phenomenon in its natural environment. This may include measuring frequencies, durations, scales, and amounts.

Secondary data is a fast, inexpensive way to conduct correlational research. However, the data may not be reliable or not entirely relevant to your study—and you have no control over it.


The goal of correlational research is to identify variables that have some sort of relationship to the extent that one creates a change in the other. 

When to Use

Correlational research is used to gather data quickly from natural settings so you can generalize findings to a real-life situation.

The following are examples of correlational research:

  • Find out if there is a relationship between Facebook shares of your website link and a higher Google ranking.
  • Discover if there is a correlation between gender and class participation in college classes by observing seminars, tracking the frequency and duration of students’ contributions, and categorizing them by gender.
  • Find out if videos on your website improve dwell time and increase conversions.

The causal-comparative research method is used to identify a cause and effect relationship between two variables, where one variable is dependent and another is independent. It has aspects in common with experimentation but cannot be considered a true experiment.

There are three main types of quasi-experimental research designs:

Nonequivalent groups: groups are similar, but only one experiences treatment or variable

Regression discontinuity: researchers assign an arbitrary cutoff in the list of participants. Those above the cutoff receive treatment or variable and those below do not. The individuals just below the threshold are used as a control group because they are so near the threshold.

Natural experiments: an external event or situation (nature) results in the random assignment of subjects to the variable recipient group. These experiments are observational and are not considered true experiments.


The goal of causal-comparative research is to identify how different groups are affected by the same circumstance.

When to Use

Causal-comparative/quasi-experimental research is often used when experimental research is deemed infeasible, unethical, or prohibited.

The following are examples of causal-comparative/quasi-experimental research:

  • Your hypothesis is that sixth-grade students who attend an afterschool program will achieve better grades. You choose two similar groups of sixth-graders who attend different schools—one with an afterschool program and one without.
  • Find the difference in wages between men and women with a comparative study of wages earned by both genders across various occupations and locations.
  • The Oregon Health Insurance Experiment famously expanded Medicaid (the US low-income public insurance program) to more low-income adults by random lottery. Researchers were able to examine the program's impact by using the eligible adults not chosen as a control group and the enrolled adults as a randomly assigned treatment group.

The experimental research method is research that is guided by a specific hypothesis or hypotheses. It is very useful for guiding decision-making. Any research conducted using the scientific method uses experimental research methods.

There are three types of experimental research designs:

Pre-experimental: a researcher observes a group or multiple groups after implementing a treatment or introducing a factor that is assumed to lead to changes in the groups. This is used to understand if further research is necessary for the observed groups.

True experimental: depends on statistical analysis to support or refute the hypothesis. The participants must be chosen in random sampling.

Quasi-experimental: participants are not chosen at random.


The goal of experimental research is to prove or disprove a specific hypothesis. It uses the scientific method to establish the cause-effect relationship among a group of variables.

When to Use

Use experimental research when you need to compare two or more groups that are experiencing different conditions. 

The following are examples of experimental research:

  • Your company wants to market your new product. You choose to run two different versions of your advertisement as part of your marketing plan. You track the performance of each ad to determine which is the most effective.
  • You take your chosen advertisement and show it to two different demographic groups to see which groups produce the best results.
  • You create multiple prototypes of a product and test performance and capability to choose the most effective design.

Data collection, the pr