Scatterplot Matrix

We set variables appropriately for the multiple linear regression model

$\displaystyle Y_j = \beta_0 + \beta_1 x_{1j} + \beta_2 x_{2j} + \cdots + \beta_k x_{kj} + \epsilon_j,
\quad j=1,\ldots,n,

starting from the Response $ Y_j$ to predictor X1 up to X9.

The set of scatterplots for each pair of variables can be produced in a matrix form for the response $ Y_j$ and the explanatory variables $ x_{1j},\ldots,x_{kj}$. Collinearity appears in such a matrix as a close linear relation between a pair of the explanatory variables.