Step
2 (C):
Before we do some modeling, we should take a look at
the remaining variables by creating a Pairwise Comparison Chart or Correlation
Color Matrix (quantitative variables only).
Question
9: (1) Create one of these graphics as a data visualization (include in
appendix). (2) Interpret your findings (i.e. should we be concern about
collinearity or multicollinearity, etc?).
|
Answer for (2): |
Hints
Correlation and Regression Study Help
A Pairwise Comparison Chart compares quantitative entities in pairs to make judgments on which pairs are preferred, or whether they are similar or not.
A Correlation Color Matrix is a table that shows the correlation coefficients the sets of quantitative variables.
For collinearity, two predictor variables in a multiple regression have a non-zero correlation. For multicollinearity, more than two variables are inter-correlated.
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