Interpret the partial regression coefficients

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An admissions counselor, examining the usefulness of x1 5 total SAT  score and x2  5 high school class rank in predicting 5 freshman grade point average (GPA) at her university, has collected the sample data shown here and listed in file XR16055. Rank in high school class is expressed as a cumulative percentile, i.e., 100.0% reflects the top of the class.

High                                                       High

Freshman          SAT,     School   Freshman   SAT,   School

GPA

Total

Rank

GPA

Total

Rank

2.66

1153

61.5

2.45

1136

45.5

2.10

1086

84.5

2.50

966

60.2

3.33

1141

92.0

2.29

1023

74.0

3.85

1237

94.4

2.24

976

86.4

2.51

1205

89.5

1.81

1066

73.0

3.22

1205

97.0

2.99

1076

55.2

2.92

1163

95.9

3.14

1152

72.1

1.95

1121

64.1

1.86

955

51.0

a. Determine the multiple regression equation and interpret the partial regression coefficients.

b. What is the estimated freshman GPA for a student who scored 1100 on the SAT exam and had a cumu- lative class rank of 80%?

c. Determine the 95% prediction interval for the GPA of the student described in part (b).

d. Determine the 95% confidence interval for the mean GPA of all students similar to the one described in part (b).

e. Determine the 95% confidence interval for the population partial regression coefficients, /31  and/32.

f. Interpret the significance tests in the computer printout.

g. Analyze the residuals. Does the analysis support the applicability of the multiple regression model to these data?

Reference no: EM13977528

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