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

question 36

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}     -State the hypotheses for testing the regression coefficient of Price. Based on the results, what do you conclude?

-State the hypotheses for testing the regression coefficient of Price. Based on the
results, what do you conclude?


Definitions:

Investment Projects

Initiatives undertaken by a business or individual involving the allocation of resources with the expectation of future benefits, such as profits or interest.

Profitability Index

Profitability Index (PI) is an investment appraisal technique that calculates the ratio between the present value of future cash flows and the initial investment cost, helping to determine the desirability of a project.

Cash Outflows

Money or funds leaving a business, typically for expenses, investments, or other payments.

Investment Projects

Initiatives or plans requiring capital investments aimed at generating future benefits or returns.

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