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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:   -Circle the standard error of the slope and its components in the output shown. If the information is not in the output, list components.
-Circle the standard error of the slope and its components in the output shown. If the
information is not in the output, list components.


Definitions:

Primary Male Sex Characteristic

Refers to the biological and physiological features present at birth that define male anatomy, including the testes and penis.

Testes

Male reproductive organs responsible for producing sperm and hormones, notably testosterone.

Penis

The male genital organ used for sexual reproduction and urination.

Primitive Testes

The early form of male gonads that develop during embryonic stages, leading to the production of sperm and secretion of male sex hormones.

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