Numerical And Categorical Data in Research – Importance & Difference

Categorical Data

Andy is working on a class project. Do you know what Andy needs to complete the project and get the desired results? Yes, you are absolutely right. Andy needs data. Now, the problem is which kind of data Andy needs. Does she need numerical data or categorical data? Well, it depends entirely on the project type and discipline. However, one thing is sure, like Andy, you also do not know what categorical and numerical data are. It is because you are here to learn about these two data types.

As you are here to learn about these two kinds of data, we will not send you empty-handed. In today’s article, we will discuss numerical and categorical data in detail. First, there will be definitions for both data types and their importance. In the end, we will discuss the differences between them. So, without wasting any time further, let’s start.

What is numerical data? Also, explain its importance.

Numerical data is any data that is in the form of numbers. It is also called quantitative data. This data differs from qualitative data, which is in the form of words, expressions, and statements. Numerical data comes in many forms. It depends entirely on the research type and which form of data you need. For example, your project is to learn the number of students who like dark chocolate over white chocolate. By carefully analyzing the research participants, you get a number in the form of a percentage, and that is your numerical data.

Numerical data is important in research because the numbers show that your research study is objective. As a researcher, you cannot manipulate the numbers and play with them as you can with qualitative data. So, it adds to the importance of numerical data.

What is categorical data? Also, explain its importance.

Categorical data is the type of data that can be stored in the form of groups in tables and rows. Each table or row is characterized by a special name or a label given to it. The data belonging to each category has certain qualities. To group this data, the technique of matching is used. The datasets which match the qualities of each other are put into one place or category. If you cannot do the matching, hire a dissertation proposal help and provide it with all the qualities. Such a dissertation help will make the data categories for you to analyze.

 Categorical data is important because it provides straightforward answers. It means that you cannot change the options once the data is provided. Another point that adds to its importance is that this data is unique and does not have the same kind of analysis techniques that can be applied to other data types.

Differences in numerical and categorical data

Numerical data provides numerical information about something. The categorical data arranges the bulk information into different groups and categories. There are many differences between these two data types. A brief description of the major ones is as follows:

The difference in data application

Being objective data, the numerical data does not have any application except telling a numerical value. For example, you can count the daily walkers in the park. It is numerical data. On the other hand, categorial data groups the walkers into different categories and reveal many hidden patterns and themes about them.

The difference in analysis methods

The second difference between numerical and categorical data lies in their analysis methods. Numerical data is data of numbers and concrete figures, and it utilizes different statistical methods. In the meantime, data based on categories does not use statistical analysis methods. To analyze this data, the techniques like matching and sorting are used.

The difference in collection methods

A huge difference lies between categorical and numerical data in terms of data collection methods. Being qualitative, you can collect categorical data with the help of surveys and questionnaires. Different data collection methods are used for numerical data and performing an experiment in the laboratory is the most popular one.

The difference in visualization

Categorical and numerical employ different data presentation and visualization techniques. If you wish to present the categories of something, a pie chart could be very useful. The reason is that the pie chart represents the whole data and serves as a reference frame. On the other hand, in the case of numerical data, you can use a scatterplot or line graph. It is because numbers are fixed points, and they need no reference.


Conclusively, numerical and categorical data are two different types of data. They are different in their collection methods, analysis methods, and visualization methods. Therefore, whenever you get to deal with such kinds of data, recall the differences that exist between them and then start the research process.

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