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Use the Regression Output Below to Answer the Following Questions (X)=( X ) =

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Use the regression output below to answer the following questions.
Lingar Reperaidion Anthyis: Dep Var (X)=( X ) = Weight
X={AX = \{ A Ee, Gender, Heifht, MBA, YY ear }\}
 Coefficients b Std.  Error  Std.  Beta t-test  Statistic p-value  Two Tailed  Intercept 210.60320.56010.2430.0000 Age 0.6600.2790.1012.3630.0186 Gender 17.4492.4500.2677.1220.0000 Height 4.9990.2940.61316.9820.0000 MBA 3.1223.0630.0431.0190.3087 Year 0.1110.5070.0060.2180.8274\begin{array}{||c|c|c|c|c|c|}\hline \text { Coefficients } & \boldsymbol{b} & \begin{array}{c}\text { Std. } \\\text { Error }\end{array} & \begin{array}{c}\text { Std. } \\\text { Beta }\end{array} & \begin{array}{c}\boldsymbol{t} \text {-test } \\\text { Statistic }\end{array} & \begin{array}{c}\boldsymbol{p} \text {-value } \\\text { Two Tailed }\end{array} \\\hline \text { Intercept } & -210.603 & 20.560 & & -10.243 & 0.0000 \\\hline \text { Age } & 0.660 & 0.279 & 0.101 & 2.363 & 0.0186 \\\hline \text { Gender } & 17.449 & 2.450 & 0.267 & 7.122 & 0.0000 \\\hline \text { Height } & 4.999 & 0.294 & 0.613 & 16.982 & 0.0000 \\\hline \text { MBA } & -3.122 & 3.063 & -0.043 & -1.019 & 0.3087 \\\hline \text { Year } & -0.111 & 0.507 & -0.006 & -0.218 & 0.8274 \\\hline\end{array}
rr2 Adj. r2SE(Reg)h0.8340.6960.69317.879448\begin{array}{|c|c|c|c|c|}\hline \boldsymbol{r} & \boldsymbol{r}^{2} & \text { Adj. } \boldsymbol{r}^{2} & \mathrm{SE}(\mathrm{Reg}) & \boldsymbol{h} \\\hline 0.834 & 0.696 & 0.693 & 17.879 & 448 \\\hline \hline\end{array}
 Source of  Variation  Sum of  Squares df Mean  Squares  F-test  Statistic p-value  One Tailed  Regression 323592.24564718.4202.4710.0000 Error 141282.23442319.643 Total 464874.47447\begin{array}{|c|c|c|c|c|c|}\hline \begin{array}{c}\text { Source of } \\\text { Variation }\end{array} & \begin{array}{c}\text { Sum of } \\\text { Squares }\end{array} & \boldsymbol{d f} & \begin{array}{c}\text { Mean } \\\text { Squares }\end{array} & \begin{array}{c}\text { F-test } \\\text { Statistic }\end{array} & \begin{array}{c}\boldsymbol{p} \text {-value } \\\text { One Tailed }\end{array} \\\hline \text { Regression } & 323592.24 & 5 & 64718.4 & 202.471 & 0.0000 \\\hline \text { Error } & 141282.23 & 442 & 319.643 & & \\\hline \text { Total } & 464874.47 & 447 & & & \\\hline\end{array}


-Based on the regression printout,what would be the predicted (mean)weight of a female,20 years old,68 inches tall,without an MBA,and in Year 1.


Definitions:

Changing Circumstances

Situations that evolve or shift, necessitating adjustments in plans, strategies, or behavior.

Verifiable Work Activities

Activities within a work or project environment that can be measured, observed, and evaluated to ensure they meet predefined standards or goals.

Performance Objectives

are specific goals related to the output or outcome of work, set to evaluate and improve the performance of individuals, teams, or organizations.

Great Goals

Represent ambitious and inspirational objectives that challenge individuals or organizations to strive for excellence and achieve significant outcomes.

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