Model B is below.
Answer 8 -10 questions please.
(8) True, model C has a higher Multiple R-squared value than
Model B, because in linear regression, every time we add a new
variable to the model, the Multiple R-squared value of the model
always keeps on increasing.
(9) True, mode C has a lower Adjusted R-squared value than Model B,
because in linear regression, the Adjusted R-squared value
decreases if we add an insignificant variable to the model. Here,
the variable "T/S ratio" is insignificant to model C. Hence, the
Adjusted R-squared value has decreased.
(10) Multiple R-squared value for Model C = 1 - (932.39/5598.1) =
0.8334 = 83.34%
C. Regression Analysis: Avg. Tot. Score versus PPS, %Takers, T/S Ratio Model Summary SR-sg R-sq (...
The regression equation is Sales = 0.20 + 2.60 Adbudget Predictor Coef SE Coef T P Constant 0.200 2.132 0.09 0.931 Adbudget 2.6000 0.6429 4.04 0.027 S = 2.03306 R-Sq = 84.5% R-Sq(adj) = 79.3% Analysis of Variance Source DF SS MS F P Regression 1 67.600 67.600 16.35 0.027 Residual Error 3 12.400 4.133 Total 4 80.000 a) What is the slope of the regression equation? b) Null and alternative hypothesis c) Is the slope significantly different than zero?...
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