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https://math.answers.com/math-and-arithmetic/Can_salary_be_numerical_or_categorical_data

Can salary be numerical or categorical data? - Answers

Salary is typically considered numerical data because it represents a measurable quantity and can be expressed in numbers. Specifically, it is continuous numerical data, as salaries can take on a wide range of values. However, in some contexts, salaries may be categorized (e.g., salary ranges or levels) for analysis, making them categorical data. Overall, the classification depends on how the data is being used or represented.



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Can salary be numerical or categorical data? - Answers

https://math.answers.com/math-and-arithmetic/Can_salary_be_numerical_or_categorical_data

Salary is typically considered numerical data because it represents a measurable quantity and can be expressed in numbers. Specifically, it is continuous numerical data, as salaries can take on a wide range of values. However, in some contexts, salaries may be categorized (e.g., salary ranges or levels) for analysis, making them categorical data. Overall, the classification depends on how the data is being used or represented.



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https://math.answers.com/math-and-arithmetic/Can_salary_be_numerical_or_categorical_data

Can salary be numerical or categorical data? - Answers

Salary is typically considered numerical data because it represents a measurable quantity and can be expressed in numbers. Specifically, it is continuous numerical data, as salaries can take on a wide range of values. However, in some contexts, salaries may be categorized (e.g., salary ranges or levels) for analysis, making them categorical data. Overall, the classification depends on how the data is being used or represented.

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      Salary is typically considered numerical data because it represents a measurable quantity and can be expressed in numbers. Specifically, it is continuous numerical data, as salaries can take on a wide range of values. However, in some contexts, salaries may be categorized (e.g., salary ranges or levels) for analysis, making them categorical data. Overall, the classification depends on how the data is being used or represented.

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