Quantitative Research Study: Definition, Approaches, Methods & Examples

What Is Quantitative Research: Definition

Before jumping into a detailed discussion on how to launch quantitative research, let’s outline a definition of this type of study. 

Quantitative research involves analyzing numerical data to uncover patterns and statistical information, which can be used to test hypotheses and respond to research questions. Quantitative methods often include statistical analysis, surveys, and experiments to generate measurable data and make accurate predictions. 

Quantitative research studies are usually applied to fields such as social science, economics, marketing, biology, etc. It is also commonly used for descriptive, correlational, or experimental studies.

Next, we will delve deeper into specific methods to define which one can best fit your academic work. However, before you start analysis and data collection, you need to be clear with the study purpose and research questions you will try to answer in your work.

>> Read more: Difference Between Qualitative and Quantitative Research

Characteristics of Quantitative Research

First, let’s define quantitative research characteristics to ensure that you choose the right type of data for your study. A deep understanding of key traits is the guarantee that you won’t make a mistake when conducting your own study.

• Quantitative data is measurable. There are variables that can be easily counted and applied to statistical formulas. In other words, this is numeric data.
• You can apply structured tools for your quantitative research. Those tools are surveys, polls, and questionnaires – structured forms you can use to collect the information.
• The sample size should be sufficient. To get accurate results, you need to collect data from a significant portion of the target market.Obtaining only 10 survey responses, for example, would not yield any meaningful insights.
• Your data can be represented in tables, graphs, or charts. As quantitative methods of data collection are focused on numbers, you should utilize visual aids to structure those numbers clearly for analysis. Such representation can provide valuable insights into patterns, trends, and relationships between independent and dependent variables.

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Quantitative Research Examples

Quite often, it is challenging to apply all the knowledge about this type of research to your specific field of study. However, we want to share examples of quantitative research that illustrate that it can be used for any purpose.

Quantitative research example 1

One common example for students is an evaluation survey after they finish a course at the university. Students usually answer some questions on a likable scale. For instance, they evaluate the quality of lectures on a scale from 1 to 10, where 10 is the highest grade. These numbers help universities to see general satisfaction from this course, define an average number of people who like the course, and run a correlation between student satisfaction by course and their grades.

Example of quantitative research 2

Another common example is customer surveys you get after purchasing something online. After the purchase, you will get an email from a retailer or brand with questions about your satisfaction. For example, you will grade on a scale from 1 to 5 how easy you could find the right size or get customer support. As a result, they get numeric data to evaluate how well their online shop works and what can be improved, make some predictions about future purchases, and use the insights for marketing purposes.

Types of Quantitative Research

There are a few different types of quantitative research that can be used for various studies. Let’s overview each type of quantitative research to understand in what circumstances and for what goals you can use each of them.

We would focus on 4 main types of quantitative approaches in data collection and analysis:

1. Descriptive study Descriptive research is used to measure variables for understanding the situation. It does not involve any manipulation of variables. In other words, descriptive studies focus on defining key statistical measures, without testing for specific data insights.
2. Correlation Correlational study is used in the quantitative research process when you need to measure a relationship between two variables and understand how one variable (for example, the age of respondents) is related to positive answers in the customer survey. Ensure you understand the difference between correlation and causation while making this kind of research.
3. Causal-comparative research Causal-comparative research is a type of non-experimental study that aims to investigate the causes behind differences in behavior among multiple groups. It is one of the commonly used types of quantitative studies for investigating  causal relationships between variables.
4. Experimental research. Experimental research involves manipulating independent variables to observe how they affect dependent variables under controlled conditions. Put simply, the researcher will need to alter the situation to measure various outcomes that may occur.

Primary Quantitative Research Methods

When discussing types of quantitative research methods, we also need to define primary and secondary methods. Primary methods are used to collect data directly from the source, such as through surveys, experiments, or systematic observations. 

Below we will explain each of these methods in detail.

1. Survey Research

Surveys are a widely used quantitative research methodology across various disciplines and fields of study. They are organized both online or offline to gather data from different audiences. In recent years, online surveys have become increasingly popular, replacing traditional methods such as phone or in-person questioning

Surveys can be applied to achieve various study aims, such as understanding attitudes, behaviors, opinions, preferences, or demographic characteristics.

We would like to define 2 main quantitative survey methods:

• Cross-sectional surveys Cross sectional survey that analyzes data across a sample population at a specific point in time. It means you may send this survey to various different groups of people, but you will need a one-time point you are researching for your study. It is a common method in such fields like economy, epidemiology, or medicine.
• Longitudinal surveys In longitudinal research, you will measure the same group of people, but the data should be collected repeatedly over time. This method requires repeated measurements at regular intervals, such as days, months, or even years, to track changes in dependent variables over time.

Survey quantitative research method example

One of the common examples is the survey for measuring how citizens are satisfied with local politicians. For this purpose, the sociology group used to develop a questionnaire sample and define target audiences – people living in specific areas or some age groups. Based on their answers, different methods can be applied to answer defined questions, make predictions for the next election or just measure the general attitude of the selected group to political ideas.

2. Experiment

Experimentation is one of the quantitative approaches to research that assumes testing various theories to prove or disprove them, or to identify their limitations. This is another powerful quantitative research method that is often used in psychology, biology, physics, and sociology, among others. 

Experimentation is a systematic quantitative research approach to testing hypotheses and understanding the causal relationships between variables. Researchers manipulate independent variables while holding all other variables constant to observe changes in their dependent variable. By comparing the outcomes of the experimental group to those of the control group, researchers can determine if intervention was effective.

There are two main types of experiments:

• Laboratory experiments A laboratory experiment is conducted in a controlled environment, such as a laboratory or research center, where researchers have complete control over the variables they manipulate. Such experiments are carefully designed to ensure that all resulting data is carefully analyzed in a lab report.
• Field experiments Field experiment is a quantitative methodology conducted in real-world settings, such as schools, businesses, or communities, where researchers have less control over variables.

Example of experiment method

You may know about such famous experiments in psychology, such as the marshmallow experiment, when children need to wait some time to eat the marshmallow. The psychologists test how the child's behavior and motivation are related to endurance. For this experiment, scientists measured an independent variable which is the number of sweeteners and dependent variables as time and children's attitude to the task.

>> Read more: How to Design an Experiment 

3. Systematic Observation

One of the most reliable types of quantitative research methodologies is systematic observation. It requires researchers to observe specific situations, behavior, or case and collect numeric data based on predefined forms. Those forms are based on the theoretical framework for a specific quantitative study. Usually, this method involves one or more observers and can be applied to different events or behavioral observations. 

Systematic observation relies on accurate coding and the proper recording of data onto the structured forms used in the study. This quantitative research method is commonly employed in fields such as sociology, medicine, education, and psychology, and requires precise numeric data to be collected. Although observations can be documented through video or audio recordings, researchers using systematic observation focus specifically on measuring specific variables of interest. 

Observation: quantitative research design example

Great example is the observation of children's behavior in the classroom. For study proposals, observers can keep an eye on a classroom during different activities. Then they add countable information into the form - how many times the teacher asked for a specific action or raised a question? How many times do children speak during the class?

Quantitative Methods for Data Collection

When we discuss various analytical techniques, we have already mentioned some types of quantitative data collection methods. However, let’s go deeper and identify key methods to gather numeric data. We will speak about sampling methods, surveys, and polls. Also, our experts prepared examples of quantitative methods for data collection to help students and researchers work accurately. You also should consider using specific tools for working with this type of data and what is the most important to understand your study purpose. 

1. Sampling Method

Let’s imagine you are conducting research about teens and their usage of social media. There is no way you can send a survey, and they analyze data from all teens in the world. However, you will need to choose a reliable number of teens and then create quantitative research designs for this group. 

There are two main sampling methods we are going to discuss – probability and non-probability sampling. 

Probability Sampling

This quantitative method of data collection can be applied to cases when you need to analyze a specific group of people. For instance, you need to learn what the chance is that a city will vote for a chosen politician. It means you need to understand the age and gender percentages in a city and choose people for the survey based on this information. If your city has 34% of women age 55+, using a quantitative approach, you need to have the same percentage in your sampling. 

There are 4 types of probability sampling:

1. Simple random sampling
2. Systematic sampling
3. Stratified sampling
4. Cluster sampling.

Non-Probability Sampling

These quantitative data collection methods consider that the choice of samples depends on a researcher's experience and knowledge. In other words, not everyone can be selected for this data collection procedure - not everyone has an equal probability of being a part of your study. 

Quantitative researchers use five models for non-probability data gathering:

• Convenience sampling: the only reason to choose study participants is their proximity to researchers.
• Quota sampling: scientists use their knowledge and experience to form a quota.
• Consecutive sampling: similar to the conventional method but can be applied to the same situation during some period of time.
• Snowball sampling: researchers ask their target audience whom they can recommend for the same study.
• Judgmental samplings: it is usually chosen based on the researcher's skills.

2. Surveys

The next and quite popular method to collect data is the quantitative survey method. The design of your question will depend on the theory you are using for your study. For instance, If you are looking at how customer awareness about product features influence their engagement with a brand, you will apply relationship communication theory. In other words, you can’t put any questions you want into the survey.

You can conduct surveys for your quantitative research using the following ways:

• Email
• Social media
• SMS
• QR-code
• Survey on your website
• Offline surveys, and other methods.

As quantitative studies are focused on numeric data, you need to use a likable scale for answers and not open questions.

3. Polls

Polls are a commonly used quantitative research method, particularly in election and exit polls. Conducting quantitative research for the election means you can ask simple questions with multiple choices. For instance, you may offer a few demographic questions (e.g., age, employment),as well as questions about voting behavior (e.g., candidate they voted for).

Applying quantitative design for polls, researchers need to ensure that the answers can be analyzed with statistical formulas. That is why the questions for the polls are often quite simple and comprise up to 5 questions. However, in some cases, polls may include even less queries. 

A quantitative research study can use benchmarks, brushfire, and tracking polls.

Data Analysis Methods

After you collect the results of your polls, samplings, or surveys, you need to analyze quantitative data. As we are discussing primary data, researchers have raw information that can be analyzed and later interpreted in different ways. 

Based on quantitative research approaches, we identify 2 key methods for the analysis of numeric data:

• Descriptive statistics Descriptive statistics allows us to get average data on questions or measure variability. It helps to overview the data with statistical evaluation. Applying descriptive statistics, you can count the average mean or standard deviation.
• Inferential statistics Inferential statistics helps to design predictions and understand the relations between variables. You can run a T-test to measure the relation between two variables. Likewise, you may arrange a Pearson correlation test and measure how one variable depends on another one.

Using these statistical instruments, scientists can go deeper into result discussion and test hypotheses.

Secondary Quantitative Research Methods

Secondary methods of quantitative research are based on the analysis of existing data – the information already gathered by someone or presented in other papers. In this case, we do not need to collect data. Instead, scientists conduct their own quantitative research applying statistical analysis methods and formulas to gain new insights from existing data. 

There are 5 most commonly used types of secondary quantitative research methods:

• Data from open online sources This is probably one of the most frequently used resources for quantitative study is the internet. A lot of companies and government institutions share the data on their own work, like the number of mobile users or a number of people using state health insurance.
• Official data from government and non-government organizations Some data can exist in official reports but are not published online. In this case, you can ask for data that can be shared without breaking privacy protection laws. You may need to make an official request for the information you want to use for your study.
• Public libraries You may think that no one uses public libraries. However, this is where you can find old studies conducted by someone else. The library also has a dataset for the papers that can be used for your own study.
• Educational institutions A lot of educational institutions are also conducting research. While you can find the analytics published in open sources, a data set can be shared with you after the request.
• Commercial sources These sources typically include information from private research firms or companies that collect and analyze data on specific industries, markets, or consumer behavior. Researchers can access this data through websites, reports, or journals, or by requesting access directly from the companies themselves.

How to Conduct Quantitative Research?

If you are working in the academic field or going to get a master's or Ph.D. degree, you definitely will need to conduct various types of studies to write a dissertation. Let’s look at the common ways to conduct quantitative research. Make sure you keep these important considerations in mind:

1. Determine the type of research you need to conduct. Will you be testing a hypothesis? If so, you will likely need to analyze numerical data.
2. Identify the appropriate sample size for your study. Do you need a large sample size to obtain reliability of outcomes, or will a smaller sample size suffice?
3. Be clear about your research goals. It's important to define your research objectives and ensure that your study design aligns with these goals.
4. Simplify your research questions. If your questions are clear and concise, it will be easier to determine the appropriate type of analysis needed to answer them.

Adhering to these recommendations ensures that research is targeted and generates valuable findings.

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Advantages of Quantitative Research

Before choosing this analytical type for your work, you need to be aware of the advantages of quantitative research methods. 

Here are the pros of using quantitative research methodologies for the research:

• Time efficiency Gathering and analyzing numerical data usually takes less time than collecting and analyzing non-numerical data.
• Reliable data Working with numbers allows for precise statistical analysis, resulting in more reliable results.
• Objectivity The absence of personal comments or interpretation in quantitative data collection reduces the possibility of bias in the results.
• Scientific approach The quantitative method is considered one of the most scientific research methods, which helps to establish credibility and believability of the results.
• Verifiability The results can be easily checked and verified by repeating the formula or analysis, ensuring the accuracy of the data.

Disadvantages of Quantitative Research

It may look like working with quantitative research can bring only pros to your study. However, there are a few cons you need to be aware of before starting your data collection. How can methodology in quantitative research become a disadvantage for your study?

• Risk of bias We mentioned that there is no way you will put your emotions into statistical formulas. But researcher experience and personal feelings can be used to form samplings. Even the daytime for data collection can influence the final results.
• Narrow focus It is possible that you can be so focused on numbers that you miss the bigger picture. Anytime you are running the numeric study, you need to look at your questions broadly. You may also need some qualitative methods to answer your research questions.
• Complexity For people who are not very good at math and statistics, it can be problematic to identify what type of numbers they need and what test should be conducted to get results.

Bottom Line on Quantitative Research

In the few paragraphs, we tried to guide you through key principles of numeric research and answer the question of what is a quantitative study and how to conduct it correctly. We identified critical approaches in collecting data for this type of analysis and outlined limitations you need to have in mind running this study. 

You also can find the best quantitative methods examples that will definitely help you with your own study. Try your best to launch a valuable and reliable study using all the knowledge on how to work with numbers!