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

question 30

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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. r2 SE(Reg)  n0.8340.6960.69317.879448\begin{array}{|c|c|c|c|c|}\hline \boldsymbol{r} & \boldsymbol{r}^{2} & \text { Adj. } \boldsymbol{r}^{2} & \text { SE(Reg) } & \boldsymbol{n} \\\hline 0.834 & 0.696 & 0.693 & 17.879 & 448 \\\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} & \text { df } & \begin{array}{c}\text { Mean } \\\text { Squares }\end{array} & \begin{array}{c}F \text {-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}

-Which variable(s) is/are (a) significant,strong predictor(s) of Weight in the regression above?


Definitions:

Hardwoods

Wood from broadleaved, typically deciduous trees, often used for high-quality furniture, flooring, and construction.

Compatible Associations

Groups or entities that can work, exist, or live together in harmony due to shared characteristics or goals.

Biodiversity

The variety of life in the world or in a particular habitat or ecosystem, including the range of species, genetic variation, and ecosystem variety.

Improved Efficiency

The enhancement of a system or process's ability to achieve a desired output with minimal input, energy, or effort.

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