The biplot (Gabriel, 1971) is a graph that represents both
variables and cases together in two dimensions. Information about the
variables is provided by the variable projections or axes. The orientation
of the axes displays the relationship between the variables and the components.
For instance, a variable that lines up with a component axis will load
heavily on that component and a variable axis that is almost perpendicular
to a component axis will not load heavily on that component. In addition
variable axes in close proximity indicate a high correlation among the
variables. For example in the biplot below, the variables *Var1*
and *Var2* are almost line up completely with the *t1* axis
thus indicating that they both load heavily on *t1*. The closeness
in proximity also indicates that they are highly correlated.

Information about the cases can also be obtained. Distances
between points, clusters of points, outliers, etc. can be quickly visualized
with this graph as they would be with a regular scatterplot. For example,
in the biplot above we can clearly discern the presence of two groups.
Also, by looking at the variable axes you can see that the two variables
responsible for this separation are *Var1 *and *Var2*.

There are two different types of biplots available. The first type of biplot is based upon the raw or unstandardized components. This graph is good at representing distances between the data points while the standardized graph is better at representing the relationships among the variables.