1. Compute the regression equation (regression coefficient and constant) using the same data from the previous question. Compute the explained variance (R Square) and the standardized regression coefficient (beta) for this model. For R Square, Sums of Squares Explained = 235.944; Sums of Squares Total = 520.
2. Given: sample R Square 0.232; SS explained = 2848.62; SS residual = 9425.25; N = 62. Test the hypotheses Ho: R square = 0; Ha: R square NE 0 at the .05 level of significance by computing the f statistic and comparing it to the appropriate f critical value.
3.Interpret the following multiple regression equation: meaning of regression constant, coefficients, and explained variance statistics. Income (in $1,000) = 2.446 + 3.628(Education) + 0.233(Occupation Status)
R Square = 0.337
PLEASE ANSWER ASAP WITH CLEAR WORK SHOWN
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