Categorical Data

Introduction

Categorical data is data divided into categories. Statistical information made up of categorical variables—data that have been divided into categories—is known as categorical data. A set of grouped data is one example. More specifically, countable qualitative data or quantitative data clustered within predetermined intervals could be used to create category data.

The information is condensed into a probability table. However, when we examine data analysis, it is referred to use the phrase “categorical data”, which is used for data sets. It should be noted that although the data set includes some categorical variables, it may also include non-categorical variables.

In this tutorial, we will discuss categorical data.

Definition

The categorical data is made up of categorical variables, which stand in for traits like a person's gender or hometown. Categorical measurements are expressed in terms of natural language descriptions but not in terms of numbers.

Categorical data can occasionally have numerical values, but those values are not mathematically meaningful.

The following are some examples of categorical data: Favourite sport, School Postcode, etc.

Types

Generally, categorical data consists of values and observations that can be categorized or grouped. Pie charts and bar graphs are the ideal visual representations of these data. Additionally, categorical information is divided into two categories −

Ordinal Data and Nominal Data

Nominal Data

• The Latin word "Nomen," which signifies name, is the root of the word "nominal."

• As a result, "named" or "labelled" data, which ignores the data's numerical values, is a type of nominal categorical data.

• Nominal data are not measurable or able to be arranged. However, nominal data can occasionally be both qualitative and quantitative. The few examples of nominal data that are frequently used include letters, words, symbols, gender, etc.

• The grouping approach is used for the analysis of these data. The percentage or frequency can be determined when the variables are put into categories. The pie chart can be used to visually present it.

Ordinal Data

• Ordinal categorical data are classified together according to a certain "scale" or "measure."

• It's possible that the scale isn't always precise or uniform.

• Usually, this type of data is measured or arranged.

• This particular category of categorical data is said to have both categorical and numerical data characteristics because numerical values are present.

• They can be examined by grouping, and bar graphs can be used to illustrate them visually.

• Examples include surveys that compare grouped data under category variables using numerical values.

Categorical Variables

• A categorical variable is a variable that accepts several values when grouped categorical data is presented under various names or labels.

• The fundamental characteristic of data that is categorized into a particular category is a categorical variable.

• Examples: Various colour shades, high-end brands, a person's blood type, etc. are examples of categorical variables.

Categorical vs Numerical Data

Categorical Data

• Data that may be categorized or classified into different categories are known as categorical data or qualitative data, such as the type of dog, the colour of the automobile, etc.

• As it validates data before classification, it is also known as qualitative data.

• Long surveys are a possibility and may turn off responders.

Numerical Data

• Data that is numerical or quantitative and uses numbers or numerical values to express the information, such as a person's height, weight, age, etc.

• As it represents quantitative values so that arithmetic operations can be applied to them, it is sometimes referred to as quantitative data.

• There are fewer concerns with survey abandonment because the engagement is quick and simple.

Solved Examples

1) Which one of the following is an appropriate categorical variable(s)?

• Age

• Product of Number Pairs

• Colour

• None

The categorical variables are age and colour.

2) Age is a nominal or ordinal categorical variable, right?

Depending on the context, age can be both nominal and ordinal.

Age falls under ordinal categorical data when it is used to represent a particular order.

Data that is "named" or "labelled" as nominal categorical data does not take into account the data's numerical values.

Age is a nominal categorical variable that is an incomparable characteristic based on the order of numerical data.

3) State whether the following statement is true or false?

According to their application in the data, some categorical variables can be both nominal and ordinal.

The given statement is true.

4) What are some instances of categorical data from the list below?

• Information on a class of six pupils' ages.

• A group of five people's hair colour.

• The locations that seven students chose for their yearly trip.

• The volume of visitors to the museum on various days of the week.

C is the best choice. The locations that seven students chose for their yearly trip.

Categorical data refers to non-numerical information that can be divided into many groupings.

5) What is the difference between ordinal and nominal categorical data?

Ordinal categorical data −

• It is a collection of ordered non-parametric data.

• Based on their numerical data, the values are classified as ordinal.

• To conduct analysis or investigations on people's thoughts or opinions, ordinal categorical data is used.

• Illustrations include, among other things, the various positions taken by pupils in a test and respondents' opinions in a poll.

Nominal categorical data −

• It is a collection of unordered, non-parametric data.

• The "names" or "labels" of the values determine whether they are considered nominal.

• Similar objects are categorized together using nominal categorical data.

• Examples include hair colour, gender, nation, and race.

Conclusion

The categorical data is made up of categorical variables, which stand in for traits like a person's gender or hometown. Categorical measurements are expressed in terms of natural language descriptions but not in terms of numbers.

Categorical data can occasionally have numerical values, but those values are not mathematically meaningful.

FAQs

1. What do you mean by categorical data?

Statistical information made up of categorical variables—data that have been divided into categories—is known as categorical data.

2. What do you mean by nominal data?

The variables are labelled using nominal data, a sort of data that doesn't assign any numerical values. Additionally called the nominal scale.

3. What is ordinal data?

Data that has a natural order is referred to as ordinal data. The distinguishing characteristics of ordinal data include the inability to distinguish between data values.

4. Can a number be classified as data?

Numbers can be used as categorical data. Categorical data can include grouping as well as numerical analysis of some common labels and numbers that reflect them.

5. What do you mean by numerical data?

Data that is numerical or quantitative and uses numbers or numerical values to express the information, such as a person's height, weight, age, etc.