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organized basketball, but did acknowledge interest and so me social participation in the game. Height (inches), weight (pounds), and speed in the 100-yard dash (seconds) were recorded for each subject. The basketball test consisted of the number of field goals that could be made in a 60-min. period. The data are given in Table 8.29. We are interested in predicting GOALMADE using some combination of WEIGHT,HEIGHT, DASH100. 1) What is the unit of measure for the regression coefficient related to HEIGHT?(Hint: Recall, Bheight is a slope) 2) Using the "Analyze" → “Multivariate Methods" →“Multivariate" commands,produce the matrix of correlations and the matrix of scatter plots for all four variables. Note that all variables will get entered into the box for "Y" in the"Multivariate" analysis. Using this output only, which of the three predictors is the single best predictor of GOAL MADE? Justify your choice, and report the R2 for thisSLR. 3) Using JMP output from above, do any of the input variables (HEIGHT, WEIGHT,DASH100) exhibit multicollinearity? 4) Now, we want to determine if the variables WEIGHT and/or HEIGHT should be added to the model that already contains DASH100 to explain GOAL MADE. Write your full and reduced models; then perform the appropriate test. (Please show your expanded ANOVA table, but you do not need to state your hypotheses explicitly.) 5) Finally (without running any mo re JMP output), determine if the variableDASH100 is useful in explaining GOAL MADE when HEIGHT and WEIGHT area already in the model. State the test-statistic, p-value, and conclusion only.

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