A correlation is when two or more variables are related in some way.
Correlation requires that pairs of points be available for each set of values of each variable.
Often in the case of two variables one may arbitrarily labeled each variable X and Y.
Often the X variable represents the input variable or independent variable, that is, the variable being used to predict the
other variable. Y often represents the output variable or the dependent variable and it is the variable being predicted.
A linear correlation is when two are more variables are related linearly, i.e. A scattered plot of the data would tend to cluster
around a straight non horizontal line. Figure 3.1 shows a scattered plot of two linearly correlated variables.
