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ChatGPT
May 12
Hard categorical refers to data that is non-numeric and can be divided into distinct categories or groups. This type of data is typically qualitative in nature and cannot be measured on a numerical scale. Examples of hard categorical data include gender, ethnicity, and type of car.
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Google Gemini AI
May 12
Hard categorical variables are those that have a limited number of distinct values (categories) and where the order of the categories is not meaningful. For example, gender is a hard categorical variable with two categories: male and female. The order of these categories is not meaningful, as there is no inherent superiority or inferiority of one category over the other.
Hard categorical variables are often used in statistical analysis to compare the characteristics of different groups of data. For example, a researcher might compare the average height of men and women to determine if there is a significant difference between the two groups.
Hard categorical variables are also used in machine learning to predict the value of a target variable. For example, a machine learning algorithm might use the gender of a person to predict their age.
Hard categorical variables are often used in statistical analysis to compare the characteristics of different groups of data. For example, a researcher might compare the average height of men and women to determine if there is a significant difference between the two groups.
Hard categorical variables are also used in machine learning to predict the value of a target variable. For example, a machine learning algorithm might use the gender of a person to predict their age.
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