Selling price and percent of advertising budget spent were entered into a multiple regression to determine what affects flat panel LCD TV sales.Using the output shown below, which of The following statements is NOT true? Response Variable is Sales $\begin{array} { l r r r r } \text { Predictor } & \text { Coef } & \text { SE Coef } & \text { T } & \text { P } \\ \text { Constant } & 90.19 & 25.08 & 3.60 & 0.001 \\ \text { Price } & - 0.03055 & 0.01005 & - 3.04 & 0.005 \\ \text { Advertising } & 3.0926 & 0.3680 & 8.40 & 0.000 \end{array}$ $S = 10.6075 \quad R - S q = 84.48 \quad R - S q ( a d j ) = 83.3 \frac { 9 } { 8 }$

A) $84.4 \%$ of the variation in TV sales are explained by the model. B) The coefficient of Price indicates that TV sales go down as Price increases. C) The standard deviation of the residuals is about 10.6. D) By the rule of thumb, the model could make errors as much as $20.2 \mathrm { TV }$ sales. E) All of the above are true. A) $84.4 \%$ of the variation in TV sales are explained by the model. B) The coefficient of Price indicates that TV sales go down as Price increases. C) The standard deviation of the residuals is about 10.6. D) By the rule of thumb, the model could make errors as much as $20.2 \mathrm { TV }$ sales. E) All of the above are true. B

Using the output below, calculate the predicted turnover rate for a company having a trust index score of 70 and an average annual bonus of $6500. Response Variable is Turnover Rate $\mathrm { R }$-squared $= 79.6$ \% $\begin{array} { l r r r r } \text { Predictor } & \text { Coef } & \text { SE Coef } & \text { T } & \text { P } \\ \text { Constant } & 12.1005 & 0.7826 & 15.46 & 0.000 \\ \text { Trust Index } & - 0.07149 & 0.01966 & - 3.64 & 0.001 \\ \text { Average Bonus } & - 0.0007216 & 0.0001481 & - 4.87 & 0.000 \end{array}$

A) $3.5 \%$ B) $4.2 \%$ C) $1.9 \%$ D) $2.4 \%$ E) None of the above. A) $3.5 \%$ B) $4.2 \%$ C) $1.9 \%$ D) $2.4 \%$ E) None of the above.

Using the output below, which is the correct interpretation of the coefficient of Average Bonus? Response Variable is Turnover Rate $\mathrm { R } -$ squared $= 79.6 \%$ $\begin{array} { l r r r r } \text { Predictor } & \text { Coef } & \text { SE Coef } & \text { T } & \text { P } \\ \text { Constant } & 2.1005 & 0.7826 & 15.46 & 0.000 \\ \text { Trust Index } & - 0.07149 & 0.01966 & - 3.64 & 0.001 \\ \text { Average Bonus } & - 0.0007216 & 0.0001481 & - 4.87 & 0.000 \end{array}$

A) For every additional $10,000 dollars in Average Bonus, the predicted Turnover Rate will go down about 7.2%. B) For every additional $10,000 dollars in Average Bonus, the predicted Turnover Rate will go up about 7.2%. C) For every additional $10,000 dollars in Average Bonus, and taking account of the other predictor (Trust Index), the predicted Turnover Rate will go down about 7.2%. D) For every additional $10,000 dollars in Average Bonus, and taking account of the other predictor (Trust Index), the predicted Turnover Rate will go up about 7.2%. E) None of the above. A) For every additional $10,000 dollars in Average Bonus, the predicted Turnover Rate will go down about 7.2%. B) For every additional $10,000 dollars in Average Bonus, the predicted Turnover Rate will go up about 7.2%. C) For every additional $10,000 dollars in Average Bonus, and taking account of the other predictor (Trust Index), the predicted Turnover Rate will go down about 7.2%. D) For every additional $10,000 dollars in Average Bonus, and taking account of the other predictor (Trust Index), the predicted Turnover Rate will go up about 7.2%. E) None of the above.