Categorical Data

Categorical Data

The data which has characteristics that represent a person’s age, behaviour, gender, or hometown is known as categorical data. These are usually expressed or resented with the help of natural language descriptions but it cannot be numbers or other special characters. Some examples of the categorical data are:

• Pincode

• Phone Number

• Year

• School they went to

• The place they were born

• Place they lived

You may notice that some of the above-mentioned categories like the age and Pincode might contain numerical as their value but this doesn’t mean that they are not categorical values. The most effective and the simplest way to find whether the given data is categorical or not, you simply find the average of the data. If you can calculate the average of a given data set, then you can consider it as numerical data. In the examples that are mentioned above, the numerical data is the pin code, the phone number, and the age because you can’t really calculate the average of pin code or phone number or year. Please note categorical and numerical data are different.

Types of Categorical Data

In Statistics, categorical data has observations and values that can be sorted in groups and categories. One of the best ways to represent this is with the help of a pie graph or a bar graph. Next, the categorical data is now divided into two different categories, namely,

• Nominal Data

• Ordinal Data

Nominal Data

Nominal Data is used to label the variables without providing any numerical value. In other words, it is also called nominal scale. Also, the nominal data cannot be ordered nor it cannot be measured. But, it can be quantitative and also quantitative. The most common examples of nominal data are:

• Words

• Symbols

• Gender

• Letters, etc.

With the help of the grouping method, you can analyse this data. The frequency or percentage is calculated after grouping the data into categories. It can be visually represented with the help of a pie chart.

Ordinal Data

Any data that follows a natural order is known as ordinal data. The vital notable feature of ordinal data is that the difference in the values cannot be found easily. You come across this kind of data during surveys, finance, economics, and questionnaire. You can analyze this data with the help of some visualisation tools such as graphs or charts. The most commonly used chart to represent ordinal data set is the bar graph. Besides that, sometimes the data can be represented using tables indicating the distinct categories. 

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Categorical Variables

In statistics, when a variable consists of a fixed number of values or a limited number of values, it is called as a categorical variable. The values can normally be variables like the blood group, labels, names, etc. Some of the examples related to categorical variables are:

• The colour of a wall, like red, blue, pink, gree, etc., - has to be described.

• Gender of people - like a male, female and transgender - cannot be anything other than this

• The blood group of a person - like A, B, O, AB, etc., cannot be anything other than this.

These variables can be assigned to another unit of observation or an individual to a particular group or a nominal category based on certain qualitative properties. Generally, each of the potential values of a categorical variable is said to be as a level. The probability distribution linked with a random categorical variable is known as categorical distribution.