A correlation matrix allows us to see lots of correlations at once, between many pairs of variables.Acorrelation matrix for several variables (Exercise, TV, Height, Weight, and GPA) in the StudentSurvey dataset is given. For any pair of variables (indicated by the row and the column), we are given two values: the correlation as the top number and the p-value for a two-tail test of the correlation right beneath it.

(a) Which two variables are most strongly positively correlated? What is the correlation? What is the p-value? What does a positive correlation mean in this situation?
(b) Which two variables are most strongly negatively correlated? What is the correlation? What is the p-value? What does a negative correlation mean in this situation?
(c) At a 5% significance level, list any pairs of variables for which there is not convincing evidence of a linear association.

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Correlations: Exercise, TV, Height, Weight, GPA TV Height Weight Exercise TV 0.010 0.852 Height 0.118 0.181 0.026 0.001 Weight 0.118 0.165 0.619 0.026 0.002 0.000 GPA -0.217 -0.159 -0.129 -0.116 0.003 0.017 0.033 0.000 Cell Contents: Pearson correlation P-Value