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Unformatted text preview: Statistics Assignment CH18 18.4 a. &#2;&#0; &#2;&#0;-1.97 The regression mod Minor HR 0.67 Age 0.14 Years Pro 1.18 b. b1=0.665838 For each additional minor league home run, the number of major league home run increases by 0.665838 provided that other variables remain con b2=0.135727 For each additional year of age of the player, the number of major league home run increases by 0.135728 provided that other variables remain con b3=1.176371 For each additional year in professional, the number of major league home run increases by 1.176371 provided that other variables remain con c. Standard Error=6.992105 R square=0.351128 (by Excel The data above tells that the model dosen't fit well. d. H0: 1= 2= 3 H1:At least one i isn't equal to 0 ANOVA SS MS F M& M& 3 3227.61 1075.87 22.01 122 5964.52 48.89 125 9192.13 P-value=0.00000 There's enough evidence to infer that the model is e. H0: i=0 H1: i &#0;-0.21 0.84-20.87 16.93-20.87 16.93 Minor HR 7.64 0.49 0.84 0.49 0.84 Age 0.26 0.8-0.9 1.17-0.9 1.17 Years Pro 1.75 0.08-0.15 2.5-0.15 2.5 Minor HR: t=7.640212, P-value=0.0000 Age: t=0.258979, P-value=0.796088 Years Pro: t=1.75414, P-value=0.081917 Only the number of home runs in minor league has a linear relationship with the h runs in major league f. Prediction Interval Major HR Predicted value 24.31 11 9670103 t M & P-M M& 95% M& 95% M& 95.0% M& 95.0% Prediction Interval Lower limit 9.86 he player will hit between 9.86 and 38.76he player will hit between 9....
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