Factors

In this exercise you dive into the wonderful world of factors.

The term factor refers to a statistical data type used to store categorical variables. The difference between a categorical variable and a continuous variable is that a categorical variable can belong to a limited number of categories. A continuous variable, on the other hand, can correspond to an infinite number of values.

It is important that R knows whether it is dealing with a continuous or a categorical variable, as the statistical models you will develop in the future treat both types differently.

A good example of a categorical variable is the variable student_status. An individual can either be "student" or "not student". This means that "student" and "not student" are two values of the categorical variable student_status and every observation can be assigned one of these values. We can do this using the factor function.

This exercise is part of the course

Inferential Statistics

View Course

Exercise instructions

Turn the vector student_status into a factor and put this in a variable called categorical_student
Print the variable categorical_student

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# a vector called student_status
student_status <- c("student", "not student", "student", "not student")

# turn student_status into a factor and save it in the variable categorical_student


# print categorical_student to the console

Edit and Run Code