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Categorical data classifies information into distinct groups or categories, lacking a specific numerical value. It refers to a form of information that can be stored and identified based on their names or labels. Categorical Data is a type of qualitative data that is easily measured numerically.
List of 22 examples of categorical data. Categorical data vs numerical data. Infographic in PDF. Let’s define it: As you might guess, categorical data is data that is divided into groups or categories. These categories are based on qualitative characteristics such as gender and colors or something else that doesn’t have a number associated with it.
Here are some examples of categorical data: Birthdate; Favorite sport; Postcode; Hair Color; Height; In the examples above, both birthdate and postcode are numbers. However, even though they include numbers, the data is categorical because it cannot be manipulated quantitatively, like figures and amounts.
Categorical variables portray a primary component in data analysis, offering invaluable insights into the qualitative nature of data, irrespective of the field of study. These variables allow data to be divided into various groups based on unique characteristics or features.
Categorical Data Examples 1. Household Income: Categorical data is mostly used by businesses when investigating the spending power of their target audience, to conclude on an affordable price for their products. For example:
Categorical data classifies items into distinct categories or labels based on qualitative characteristics, making it suitable for organizing and summarizing data. There are two main types of categorical data: nominal and ordinal.
1. Nominal Variables: These are the simplest form of categorical data. Nominal variables represent discrete categories that do not have any inherent order. For instance, the colors of a rainbow (red, orange, yellow, green, blue, indigo, violet) are nominal, as there is no intrinsic ranking or order. 2.
Categorical Variables: Variables that take on names or labels. Examples include: Marital status (“married”, “single”, “divorced”) Smoking status (“smoker”, “non-smoker”) Eye color (“blue”, “green”, “hazel”) Level of education (e.g. “high school”, “Bachelor’s degree”, “Master’s degree”)
Examples of Categorical Data. Marketing and Consumer Behaviour. Healthcare and Medical Research. Surveys and Opinion Polls. Importance of Categorical Data Analysis. Unlocking Insights into Human Behaviour. Identifying Patterns and Associations. Driving Data-Driven Decision Making. Summary. Types of Categorical Data.
Surveys, like the ones we see on the television show Family Feud or the frequency of people with various eye colors, are examples of categorical data. In this chapter, there are two types of categorical data that we consider: ordinal data and nominal data.