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As Part of a Study at a Large University, Data x1=x _ { 1 } =

question 31

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As part of a study at a large university, data were collected on n = 224 freshmen computer science (CS) majors in a particular year. The researchers were interested in modeling y, a studentʹs grade
Point average (GPA) after three semesters, as a function of the following independent variables
(recorded at the time the students enrolled in the university) : x1=x _ { 1 } = average high school grade in mathematics (HSM)
x2=x _ { 2 } = average high school grade in science (HSS)
x3=x _ { 3 } = average high school grade in English (HSE)
x4=x _ { 4 } = SAT mathematics score (SATM)
x5=x _ { 5 } = SAT verbal score (SATV)
A first-order model was fit to data with the following results:
 SOURCE  DF  SS  MS  FVALUE  PROB >F  MODEL 528.645.7311.69.0001 ERROR 218106.820.49 TOTAL 223135.46\begin{array}{lrrrrr}\hline \text { SOURCE } & \text { DF } & \text { SS } & \text { MS } & \text { FVALUE } & \text { PROB >F } \\\text { MODEL } & 5 & 28.64 & 5.73 & 11.69 & .0001 \\\text { ERROR } & 218 & 106.82 & 0.49 & & \\\text { TOTAL } & 223 & 135.46 & & &\end{array}

 ROOT MSE 0.700 R-SQUARE 0.211 DEP MEAN 4.635 ADJ R-SQ 0.193\begin{array}{llll}\text { ROOT MSE } & 0.700 & \text { R-SQUARE } & 0.211 \\\text { DEP MEAN } & 4.635 & \text { ADJ R-SQ } & 0.193\end{array}

 As part of a study at a large university, data were collected on n = 224 freshmen computer science (CS) majors in a particular year. The researchers were interested in modeling y, a studentʹs grade Point average (GPA) after three semesters, as a function of the following independent variables (recorded at the time the students enrolled in the university) :  x _ { 1 } =  average high school grade in mathematics (HSM)   x _ { 2 } =  average high school grade in science (HSS)   x _ { 3 } =  average high school grade in English (HSE)   x _ { 4 } =  SAT mathematics score (SATM)   x _ { 5 } =  SAT verbal score (SATV)  A first-order model was fit to data with the following results:  \begin{array}{lrrrrr} \hline \text { SOURCE } & \text { DF } & \text { SS } & \text { MS } & \text { FVALUE } & \text { PROB >F } \\ \text { MODEL } & 5 & 28.64 & 5.73 & 11.69 & .0001 \\ \text { ERROR } & 218 & 106.82 & 0.49 & & \\ \text { TOTAL } & 223 & 135.46 & & & \end{array}    \begin{array}{llll} \text { ROOT MSE } & 0.700 & \text { R-SQUARE } & 0.211 \\ \text { DEP MEAN } & 4.635 & \text { ADJ R-SQ } & 0.193 \end{array}         Interpret the value under the column heading  \mathrm { PROB } > \mathrm { F } . A)  Accept  H _ { 0 }  (at  \alpha = .01  ) ; at least one of the  \beta -coefficients in the first-order model is equal to 0 . B)  There is insufficient evidence (at  \alpha = .01  )  to conclude that the first-order model is statistically useful for predicting GPA. C)  Over  99 \%  of the variation in GPAs can be explained by the model. D)  There is sufficient evidence (at  \alpha = .01  )  to conclude that the first-order model is statistically useful for predicting GPA.



Interpret the value under the column heading PROB>F\mathrm { PROB } > \mathrm { F } .


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