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Step-by-step explanation:

Data types are an important aspect of statistical analysis, which needs to be understood to correctly apply statistical methods to your data. There are 2 main types of data, namely; categorical data and numerical data.

As an individual who works with categorical data and numerical data, it is important to properly understand the difference and similarities between the two data types. This will make it easy for you to correctly collect, use, and analyze them.

The importance of understanding the different data types in statistics cannot be overemphasized. Therefore, in this article, we will be studying at the two main types of data- including their similarities and differences.

What is Categorical Data?

Categorical data is a type of data that can be stored into groups or categories with the aid of names or labels. This grouping is usually made according to the data characteristics and similarities of these characteristics through a method known as matching.

Also known as qualitative data, each element of a categorical dataset can be placed in only one category according to its qualities, where each of the categories is mutually exclusive. For example, gender is a categorical data because it can be categorized into male and female according to some unique qualities possessed by each gender.

There are 2 main types of categorical data, namely; nominal data and ordinal data.