# Variables ¶

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Variables are the columns of our matrix, basically the properties of the individuals we are observing. They can be quantitative or qualitative.

A quantitative variable is a measurement, for instance, if we took two values, we can subtract them (to compare them).

• continue: can take an infinite number of values
• discrete: can take a finite number of values
ex: age, size, score, ...


A qualitative variable (catégorielles) is either

• binary: taking values like 0 or 1, true or false
• ordered: the values are sorted like easy < medium < hard
• not ordered: the rest

## Variables in R ¶

Qualitative variables are usually from the factor class.

# get information about the variable types
str(iris)
# 'data.frame':	150 obs. of  5 variables:
#  $Sepal.Length: num 5.1 4.9 4.7 4.6 5 5.4 4.6 5 4.4 4.9 ... #$ Sepal.Width : num  3.5 3 3.2 3.1 3.6 3.9 3.4 3.4 2.9 3.1 ...
#  $Petal.Length: num 1.4 1.4 1.3 1.5 1.4 1.7 1.4 1.5 1.4 1.5 ... #$ Petal.Width : num  0.2 0.2 0.2 0.2 0.2 0.4 0.3 0.2 0.2 0.1 ...
#  $Species : Factor w/ 3 levels "setosa","versicolor",..: 1 1 1 1 1 1 1 1 1 1 ...  A factor is a variable that got levels (the unique values), and you can order the levels. levels(iris$Species)
# [1] "setosa" "versicolor" "virginica"


Here you can read that as "setosa" > "versicolor" > "virginica", but that doesn't make sense here, since this does not seem like an ordered qualitative variable.