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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:

Behaviorist Theory

A theory of learning which states that behaviors are learned from the environment through the processes of conditioning.

Rewards and Punishments

Behavioral tools used to reinforce desired behaviors or diminish undesired ones, often employed in educational and developmental contexts.

Learning

A relatively permanent change in behavior brought about by making associations between behavior and events in the environment.

Psychosexual Stages

A theory by Freud describing the stages of a child's development from birth to adulthood, through which sexual energy (libido) is focused on different erogenous zones.

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