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
Exercise instructions
- Turn the vector
student_status
into a factor and put this in a variable calledcategorical_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