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Use the Following Information for Problems
Sales Figures (Number 1 s1 \mathrm {~s}

question 26

Essay

Use the following information for problems
Sales figures (number of units), selling price and amount spent on advertising (as a percentage of total advertising expenditure in the previous quarter) for the popular Sony Bravia Television were obtained for last quarter from a sample of 30 different stores. The results of a multiple regression are presented below. Dependent Variable 1 s1 \mathrm {~s} Sales
 Predictor  Coef  sE Coef  T  P  Constant 90.1925.083.600.001 Price =0.030550.010053.040.005 Advertising 3.09260.36808.400.000\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=10.6075RSq=84.4RSq(adj)=83.3÷76S = 10.6075 \quad R - S q = 84.4 \leqslant \quad R - S q ( a d j ) = 83.3 \div \frac { 7 } { 6 }
Analyaia of Variance
 Source  DF  SS  MS  Regresgion 216477.38238.7 Residual Error 273038.0112.5 Total 2919515.4\begin{array} { l r r r } \text { Source } & \text { DF } & \text { SS } & \text { MS } \\ \text { Regresgion } & 2 & 16477.3 & 8238.7 \\ \text { Residual Error } & 27 & 3038.0 & 112.5 \\ \text { Total } & 29 & 19515.4 & \end{array}
 Use the following information for problems  Sales figures (number of units), selling price and amount spent on advertising (as a percentage of total advertising expenditure in the previous quarter) for the popular Sony Bravia Television were obtained for last quarter from a sample of 30 different stores. The results of a multiple regression are presented below. Dependent Variable  1 \mathrm {~s}  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 = 84.4 \leqslant \quad R - S q ( a d j ) = 83.3 \div \frac { 7 } { 6 }  Analyaia of Variance  \begin{array} { l r r r } \text { Source } & \text { DF } & \text { SS } & \text { MS } \\ \text { Regresgion } & 2 & 16477.3 & 8238.7 \\ \text { Residual Error } & 27 & 3038.0 & 112.5 \\ \text { Total } & 29 & 19515.4 & \end{array}     -Report the adjusted R2 for this model. Write a sentence interpreting this value.

-Report the adjusted R2 for this model. Write a sentence interpreting this value.


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