Categorical Vs. Quantitative Data

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What is Categorical Data?

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Categorical data represents characteristics or qualities that can be divided into groups or categories. Examples include favorite food, college major, or agree/disagree responses.

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What is Quantitative Data?

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Quantitative data represents numerical values that can be measured or counted. Examples include weight, years of schooling completed, or height.

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Give an example of Categorical Data.

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An example of categorical data is 'Favorite Food' which can include categories like pizza, sushi, or pasta.

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Give an example of Quantitative Data.

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An example of quantitative data is 'Weight' which can be measured in pounds or kilograms.

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What type of data is 'Agree/Disagree'?

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Agree/Disagree is categorical data as it represents a qualitative response.

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What type of data is 'Years of schooling completed'?

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Years of schooling completed is quantitative data as it represents a numerical value.

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How can you differentiate between Categorical and Quantitative Data?

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Categorical data can be divided into groups, while quantitative data consists of measurable numbers.

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What is a common mistake when identifying data types?

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A common mistake is confusing categorical data with ordinal data, which has a specific order (e.g., ratings from 1 to 5).

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What is an example of Ordinal Data?

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An example of ordinal data is a survey response scale like 'satisfied', 'neutral', 'dissatisfied'.

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Can Categorical Data be numerical?

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Yes, categorical data can be numerical if the numbers represent categories, such as jersey numbers in sports.