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a Sales Manager Was =0.48+7.42= - 0.48 + 7.42

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Use the following for questions
A sales manager was interested in determining if there is a relationship between college GPA and sales performance among salespeople hired within the last year. A sample of recently hired salespeople was selected and college GPA and the number of units sold last month recorded. Below are the scatterplot, regression results, and residual plots for these data. The regression equation is
Units Sold =0.48+7.42= - 0.48 + 7.42 GPA
 Predictor  Coef  SE Coef  T  P  Constant 0.4843.2560.150.884 GPA 7.4231.0447.110.000\begin{array} { l r r r r } \text { Predictor } & \text { Coef } & \text { SE Coef } & \text { T } & \text { P } \\ \text { Constant } & - 0.484 & 3.256 & - 0.15 & 0.884 \\ \text { GPA } & 7.423 & 1.044 & 7.11 & 0.000 \end{array}
S=1.57429RSq=78.3%RSq(adj)=76.8%\mathrm { S } = 1.57429 \quad \mathrm { R } - \mathrm { Sq } = 78.3 \% \mathrm { \circ } \quad \mathrm { R } - \mathrm { Sq } ( \mathrm { adj } ) = 76.8 \%
Analysis of Variance
 Source  DF  SS  MS  F  P  Regression 1125.30125.3050.560.000 Residual Error 1434.702.48 Total 15160.00\begin{array} { l r r r r r } \text { Source } & \text { DF } & \text { SS } & \text { MS } & \text { F } & \text { P } \\ \text { Regression } & 1 & 125.30 & 125.30 & 50.56 & 0.000 \\ \text { Residual Error } & 14 & 34.70 & 2.48 & & \\ \text { Total } & 15 & 160.00 & & & \end{array} Answer:  Use the following for questions  A sales manager was interested in determining if there is a relationship between college GPA and sales performance among salespeople hired within the last year. A sample of recently hired salespeople was selected and college GPA and the number of units sold last month recorded. Below are the scatterplot, regression results, and residual plots for these data. The regression equation is Units Sold  = - 0.48 + 7.42  GPA  \begin{array} { l r r r r } \text { Predictor } & \text { Coef } & \text { SE Coef } & \text { T } & \text { P } \\ \text { Constant } & - 0.484 & 3.256 & - 0.15 & 0.884 \\ \text { GPA } & 7.423 & 1.044 & 7.11 & 0.000 \end{array}   \mathrm { S } = 1.57429 \quad \mathrm { R } - \mathrm { Sq } = 78.3 \% \mathrm { \circ } \quad \mathrm { R } - \mathrm { Sq } ( \mathrm { adj } ) = 76.8 \%  Analysis of Variance  \begin{array} { l r r r r r } \text { Source } & \text { DF } & \text { SS } & \text { MS } & \text { F } & \text { P } \\ \text { Regression } & 1 & 125.30 & 125.30 & 50.56 & 0.000 \\ \text { Residual Error } & 14 & 34.70 & 2.48 & & \\ \text { Total } & 15 & 160.00 & & & \end{array}  Answer:   -Test the hypotheses about the slope of the regression line. Give the appropriate test statistic, associated P-value, and conclusion in terms of the problem.
-Test the hypotheses about the slope of the regression line. Give the appropriate test
statistic, associated P-value, and conclusion in terms of the problem.


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