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 Coding for Categorical Variables in Regression Models R Learning Modules 1 The factor function # creating the factor variable hsb2$racef < factor(hsb2$race) isfactor(hsb2$racef) ## 1 2 Using the C function The C function (this must be a uppercase "C") allows you to create several

Categorical variable in research examples- In this article, we will learn how to create categorical variables in the R Programming language In statistics, variables can be divided into two categories, ie, categorical variables and quantitative variables The variables which consist of numerical quantifiable values are known as quantitative variables and a categorical variable is a variable that can take on one of a limited, In this example, hours is a continuous variable but program is a categorical variable that can take on three possible categories program 1, program 2, or program 3 In order to fit this regression model and tell R that the variable "program" is a categorical variable, we must use asfactor() to convert it to a factor and then fit the model

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 Categorical Variable Regression using R Variables that classify observations into categories are categorical variables (also known as factors or qualitative variables) They have a limited number,Example 1 illustrates how to convert a categorical vector to numeric in R For this, we first have to create an example vector x < factor ( c ( "cat_a" , "cat_b" , "cat_a" , # Create categorical vector "cat_c" , "cat_b" , "cat_b" ) ) x # Print categorical vector # 1 cat_a cat_b cat_a cat_c cat_b cat_b # Levels cat_a cat_b cat_c

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