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As Part of a Study at a Large University, Data

question 67

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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 student's 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= average high school grade in mathematics (HSM) x2= average high school grade in science (HSS) x3= average high school grade in English (HSE) x4= SAT mathematics score (SATM) x5= SAT verbal score (SATV) \begin{array}{l}x_{1}=\text { average high school grade in mathematics (HSM) } \\x_{2}=\text { average high school grade in science (HSS) } \\x_{3}=\text { average high school grade in English (HSE) } \\x_{4}=\text { SAT mathematics score (SATM) } \\x_{5}=\text { SAT verbal score (SATV) }\end{array}

 A first-order model was fit to the data with the following results: \text { A first-order model was fit to the data with the following results: }

 SOURCE  DF  SS  MS  F VALUE  PROB > F  MODEL 528.645.7311.69.0001 ERROR 218106.820.49 TOTAL 223135.46\begin{array}{llllll}\hline \text { SOURCE } & \text { DF } & \text { SS } & \text { MS } & \text { F VALUE } & \text { PROB }>\text { 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}

 PARAMETER STANDARD TFOR O:  VARIABLE  ESTIMATE  ERROR  PARAMETER =0 PROB >T INTERCEPT 2.3270.0395.8170.0001 X1 (HSM) 0.1460.0373.7180.0003 X2 (HSS) 0.0360.0380.9500.3432 X3 (HSE) 0.0550.0401.3970.1637 X4 (SATM) 0.000940.000681.3760.1702 X5 (SATV) 0.000410.00590.6890.4915\begin{array}{lrrrr}&\text { PARAMETER}&\text { STANDARD}&\text { TFOR O: }\\\text { VARIABLE } & \text { ESTIMATE }&\text { ERROR } & \text { PARAMETER }=0 & \text { PROB }>|T|\\\\\text { INTERCEPT } & 2.327 & 0.039 & 5.817 & 0.0001 \\\text { X1 (HSM) } & 0.146 & 0.037 & 3.718 & 0.0003 \\\text { X2 (HSS) } & 0.036 & 0.038 & 0.950 & 0.3432 \\\text { X3 (HSE) } & 0.055 & 0.040 & 1.397 & 0.1637 \\\text { X4 (SATM) } & 0.00094 & 0.00068 & 1.376 & 0.1702 \\\text { X5 (SATV) } & -0.00041 & 0.0059 & -0.689 & 0.4915\\\hline \end{array}

 Test to determine if the model is adequate for predicting GPA. Use α=.01\text { Test to determine if the model is adequate for predicting GPA. Use } \alpha=.01 \text {. }


Definitions:

Monitoring

The systematic observation, tracking, and evaluation of activities, progress, or performance to ensure objectives are met.

Manager's Organizational Unit

A specific section or department within an organization that is led and overseen by a manager.

Performance Of Subordinates

The level of efficiency and effectiveness demonstrated by employees in achieving their job responsibilities.

External Monitoring

The process of periodically reviewing and assessing the external environment to understand opportunities and threats relevant to an organization's objectives.

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