Quantitative Research: Definition, Types, Methods, & Examples

Quantitative research is more than just numbers! Here, you can use your math skills to gather evidence, analyze data and communicate results with others.

Quantitative research is used for collecting and analyzing data through surveys or experiments. It's different from qualitative methods, which rely on nonnumerical information like interviews or observations.

Conducting this type of research is difficult, time-consuming work that requires students to spend plenty of hours collecting numerical data. But, they should dedicate themselves fully if their goal is to complete this academic endeavor.

Continue reading this blog to learn about quantitative research basics, its types, and methods.

Quantitative Research Definition

What is quantitative research?

A systematic investigation of the world by gathering quantifiable data and performing statistical, mathematical, or computational techniques is called quantitative research.

You can collect information from existing and potential customers using sampling methods like online polls or questionnaires with quantitative research. This research attempts to capture and understand its subject matters in the truest reality and natural setting.

The future is always uncertain, but with this knowledge, we can make smart decisions to ensure success.

The templates can be used to help you in your research projects. They are objective, elaborate, and often investigational!

The most important thing to take away from this research method is how logical and unbiased the results are.

The data collection process is structured and conducted on a larger scale to represent the entire population.

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Quantitative Research Characteristics

Here are some characteristics of quantitative research.

• Extensive Sample - Using a large sample size, this study represents the people whose findings will most impact.
• Inclusive Results - The results of this experiment could be applied to a wide population.
• Closed-ended Questions - Asking research questions is one of the most important aspects of any type or form of research. Here, the questions are objective-type, so they either have ‘Yes’ or ‘No. This helps collect extensive data about the respondents' opinions on different matters.

The more specific and focused questions are, the better your chances turn out to be successful!

• Methodical Tools - Methodical tools are a great way to collect quantitative data, such as surveys and polls. The use of these data collection tools helps gather more accurate and detailed information.
• Previous Research - It is important to conduct thorough research and study the results of previous studies before you begin your experiment.

These characteristics distinguish quantitative research from qualitative research.

Types of Quantitative Research Methods

‘What are the four types of quantitative research?’

In the field of quantitative research, there are four distinct types. These methods have been given equal importance by scientists as a primary source for data collection and analysis.

Primary quantitative research is more common and useful than secondary methods.

Primary quantitative research is the most common and useful than secondary methods. It's because, in this method, you collect your data directly from respondents rather than relying on secondary sources.

It does not rely on previous research and gathers data from the start to the end.

The quantitative research design types are listed below.

1. Survey Research

Online surveys and questionnaires are the most common way to conduct this type of research. The survey is a popular method for understanding customers and their needs. The information gathered from this type of research helps organizations improve what they do.

The most common types of surveys are listed below.

• Cross-Sectional Survey - This research is conducted on the selected group of people at a certain point in time. It offers insights into how they think. The chosen group of people have many similarities in all aspects except for those that the researcher omitted.

Small-scale businesses, retail, and healthcare industries are all interested in this research.

• Longitudinal Survey - The researchers designed this study to observe a specific group of people for a set period. It could be days, months, or even years. The researcher observes how people's behavior changes over time.

This kind of research is used in medicine and marketing to applied sciences.

2. Experimental Research

In this kind of research, the goal is to prove or disprove a theory. This research is also known as true experimentation. It usually involves single or multiple theories.

This research method is a commonly used tool in natural sciences, but it has not been proven yet.

Some theories are involved in this research. Due to this, it is more common in social sciences rather than natural science or humanities.

3. Causal-comparative Research

This research is a type of study that uses the cause and effect relationship between dependent and independent variables. It is also known as quasi-experimental research.

One of the variables is dependent on another, but one cannot be changed without affecting the other. Researchers study this relationship to determine why certain behaviors change depending on different factors.

Research is not limited to statistical analysis only but includes other groups and variables. This research can be conducted on independent and dependent variables regardless of the kind of their relation.

This statistical analysis method allows you to acquire the results with a high degree of accuracy.

4. Correlational Research

Correlational research is conducted to establish the relationship between two entities. These entities must have a significant impact on each other.

This research is designed to identify, evaluate and understand the correlation between variables. The researchers use math and statistics to understand this correlation. Factors like relationships and trends may play a role in driving the variables.

Sometimes, the researchers will change one variable to see how it affects another.

Types of Data Collection Methodologies

Finding the right data collection method is crucial after determining your research type. For example, polling and sampling are both a way to gather data.

Sampling Data Collection Method

There are two types of sampling methods used in quantitative research: probability sampling and non-probability sampling.

1. Probability Sampling

The data is collected by taking some individuals from the general population and creating samples. The data samples are chosen at random and without any particular selection criteria.

Probability sampling is further classified as follows.

• Simple Random Sampling - In this kind of sampling, the participants are randomly chosen. This method is conducted on a large population, so it's more likely to get good data from all parts of society.
• Systematic Sampling - The samples from the population are chosen at regular intervals to provide an accurate portrayal. The intervals are predefined and calculated based on your target sample’s size.
• Cluster Sampling - In cluster sampling, the population is divided into several groups representing different areas and demographics.
• Stratified Random Sampling - The participants in this study are chosen randomly from several strata and groups.

2. Nonprobability Sampling

In this type of research, the researcher uses their knowledge and experience to choose samples. The researcher ensures that only specific people get chosen and sets out the criteria for this research.

• Convenience Sampling - The samples of this kind are probably the easiest to get. Samples are usually close to the researcher, and these samples can be worked with because there are no rigid parameters.
• Judgemental Sampling - The types of samples used in a study depend on the researcher's skills, experience, and preference.
• Quota Sampling - Researchers identify specific elements in the content based on their target audience and traits. According to this, the chances of being selected are equal among different individuals.
• Consecutive Sampling - It is similar to convenience sampling, but instead of choosing people at random, the researcher chooses one specific group. It repeats the experiment with different populations to get better results.
• Snowball Sampling - This kind of sampling is done on a targeted audience or group that's hard to reach.

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Survey and Polls Data Collection Method

After the researcher has chosen a sample or group, they could use polls to collect necessary data. In this research method, the data is collected from a selected group.

The data is used for various purposes, such as identifying trends and collecting information about different things. Through this survey, we can reach many more people!

The more time you spend researching, the better.

Researchers use four different criteria to measure question responses. These include nominal, interval, ordinal, and ratio scales. This research could not be created without them in the first place!

The questions used for the survey must be close-ended. These could be a mix of different kinds of questions. Also, you should respond to rating scales so that your research is analyzed correctly.

When it comes to surveying your customers, there are several different methods that you can use. Below is information on how some companies distribute surveys and ask their target audience for the feedback!

Some of the most common survey distribution methods of research are listed below.

• Social Distribution - You can take advantage of social media to collect more responses for your survey.
• Email - The most common way to distribute your survey is by email management software.
• SMS Survey - SMS survey has made it easier than ever to collect data.
• Buying the Respondents - This survey distribution method uses respondents' knowledge to maximize results.
• QR code - A survey can be printed on business cards or magazines.
• Embedding the Survey on a Website - It is an innovative and creative way to get more responses. You can get more responses and targeted results by embedding the survey on your website. You're close to customers, which is perfect for collecting feedback!

Quantitative Research Data Analysis Techniques

Data analysis is the third important aspect of quantitative research. When analyzing, it's crucial that results are relevant and related to your objective.

The following are some common statistical analysis methods for analyzing the collected data.

• SWOT Analysis - It is an acronym that stands for Strengths, Weaknesses, Opportunities, and Threats. It stands for Strengths, Weakness, Opportunities, and Threat. Businesses use this kind of analysis to evaluate their performance and develop appropriate strategies.
• Conjoint Analysis - The analysis of this kind helps businesses to identify how customers make difficult purchasing decisions.
• Cross-tabulation - A preliminary statistical analysis is an important part of the research process. This helps you understand patterns, trends, and relationships between various factors.
• Turf Analysis - It stands for Totally Unduplicated Reach and Frequency Analysis. It allows for the collection and analysis of data, responding from a chosen or favored target group.

After that, other methods, such as inferential statistics, could collect the results.

Difference between Qualitative and Quantitative Research

There are two types of research: quantitative and qualitative. They are mostly used in subjects with detailed research patterns. So what distinguishes it from quantitative research? A detailed comparison of the two types of research is provided below.

Quantitative Research vs Qualitative Research

Advantages of Quantitative Research

Researchers benefit from quantitative research in a variety of ways. Here are some strengths of quantitative research everyone must know:

• Straightforward Analysis - Data collection is straightforward with the use of statistical tests. As it eliminates any subjectivity in determining which statistical tests are appropriate.

When you have straightforward results with no uncertainty, interpreting your findings becomes easy and accurate.

• Can Be Tested and Checked - Quantitative research is reliable because it requires careful experimental design. Also, it has the ability to replicate both tests and results. You can reduce the amount of bias in your data by making sure it's more objective and transparent.
• Prestige - Knowing how to do complex data analysis is impressive and valuable because not everyone understands maths and statistics. Quantitative research is used in all business areas, from picking stocks to evaluating portfolios. The association of prestige and value with quantitative research can be a great incentive for your small businesses.

Researchers are very well aware of the importance of quantitative research. This is the reason why researchers prefer to use quantitative research methods.

It is simple to sample, collect, and analyze data and repeat the procedure.

Disadvantages of Quantitative Research

Some common quantitative research limitations are listed below.

• Difficulty in Developing a Research Model - A researcher should be careful when setting up a model for collecting and analyzing data. If there are errors in quantitative research design or mistakes committed during execution, all results should be disregarded as invalid.

A quantitative study needs to be carefully planned out to avoid leading you astray with inaccurate information.

To get an accurate answer, you must develop a hypothesis based on the data and evidence.

• False Emphasis on Numbers - The quest for concrete, statistical relationships can limit the scope of quantitative research. This pursuit is often at odds with exploring broader themes and understanding how they interact with one another.

Focusing only on numbers is a one-sided approach that can blind you from valuable information.

• Can Be Misleading - Many people believe that quantitative research is more credible or scientific than observational, qualitative work. However, the two types of study can often lead to misleading information due to their subjective nature and reliance on statistics.

Researchers are biased creatures who carry the wisdom of their experiences and beliefs. This means that any opinion or bias they have will impact data-gathering.

For these reasons, quantitative research is not an ideal choice for in-depth studies.

Now that you've learned about the strengths and weaknesses of quantitative research, use it wisely.

Quantitative Research Examples

Here are some examples of quantitative research to help you understand it better.

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