Basically the data from a quantitative survey is divided into **continuous** and **discreet**. The first is defined as **any value between two limits any**, such as a diameter. So it is a value to be "broken". It is continuous data, issues that involve age, income, spending, sales, billing, among many others.

When speaking of discrete values, one approaches **an exact value**, such as quantity of defective parts. This type of variable is commonly used to address child numbers, satisfaction and overall nominal scales.

The typology of the data determines the variable, so it will be continuous or discrete. This means that by defining a variable with continuous or discrete, in the future it has already been defined what kind of treatment will be given to it. For example, the dependent variable in an analysis involving Anova cannot be discrete.

Next: Types of Scalar Variables