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

Description

The function factor is used to encode a vector as a factor (the terms ‘category’ and ‘enumerated type’ are also used for factors). If argumentordered is TRUE,  the factor levels are assumed to be ordered. For compatibility with S there is also a function ordered.

 # turn student_status into a factor and save it in the variable categorical_student
> categorical_student<-as.factor(student_status)
> 
> # print categorical_student to the console
> categorical_student
[1] student     not student student     not student
Levels: not student student
>