Matrix Plots - Introduction

Matrix Plots

Introduction

A Matrix plot is a kind of Scatter Plot which enables the user to see the pairwise relationships between variables. XLMiner™ allows eight variables to be plotted against each other at a time.

Given a set of variables Var1, Var2, Var3, .... the matrix plot contains all the pairwise scatter plots of the variables on a single page in a matrix format. The matrix plot is a square matrix where the names of the variables are on the diagonals and scatter plots everywhere else. That is, if there are k variables, the scatter plot matrix will have k rows and k columns and the ith row and jth column of this matrix is a plot of Var_i versus Var_j. The axes and the values of the variables appear at the edge of the respective row or the column. One can observe the behavior of variables with one another at a glance. The comparison of the variables under study and their interaction with one another can be studied easily. This is why the matrix plots are becoming increasingly common in general purpose statistical software programs.

See the matrix plot below:-

The plot is drawn for two variables, VAR1 and VAR2. For the plot in the top right corner, VAR1 values are obtained on the vertical axis and VAR2 values on the horizontal axis. (Note that , the actual VAR2 values can be obtained by multiplying the value on the axis by 10² ie 100. The plot at the bottom left corner drawn by taking VAR2 on the vertical axis (remember again, the multiplying factor, 10²).

In similar manner matrix plots of three or four variables can be obtained.

See above the matrix plot with four variables. Try to identify the pair of variables used in each of the individual plots. eg. The plot in the first row and third column is drawn for variables VAR1 and VAR3. The axes for this plot will be the one at the end of the first row and the one at the end of the third column. The multiplication factor will always be applied in case of VAR2 and VAR4. You will appreciate that the above plot gives a complete picture of pairwise relationship between four variables at a glance.