The University Secretary wants to determine how University grade point average, GPA (highest being 4.0) of a sample of students from the University depends on a student’s high school GPA (HS), age of a student (A), achievement test score (AS), average number of lectures skipped each week (S), gender of a student (where M=1 if a student is male or 0 otherwise), computer or PC ownership of a student (where PC=1 if a student owns a computer or 0 otherwise), the means of transport to school (drive, bicycle or walk; where D=1 if a student drives to campus or 0 otherwise, B=1 if a student bicycles to campus or 0 otherwise), and finally, the subject major of the student (finance, human resource, marketing and accounting; where F=1 if a student majors in finance or 0 otherwise, HR=1 if a student majors in human resource or 0 otherwise, MR=1 if a student majors in marketing or 0 otherwise). Use the correlation matrix and dummy regression output to answer the questions. GPA HS A AS S M PC D B F HR MR GPA 1.00 HS 0.41 1.00 A -0.02 -0.26 1.00 AS 0.21 0.35 -0.08 1.00 S -0.26 -0.09 -0.08 0.12 1.00 M -0.08 -0.21 0.04 0.18 0.20 1.00 PC 0.22 0.04 -0.09 0.04 -0.21 -0.07 1.00 D -0.11 -0.19 0.27 -0.20 0.26 -0.08 0.02 1.00 B 0.08 0.14 -0.05 0.16 -0.13 0.13 -0.10 -0.38 1.00 F 0.08 0.12 -0.22 0.18 0.06 0.04 0.08 -0.08 -0.11 1.00 HR 0.08 0.17 -0.49 0.08 0.06 0.05 -0.04 -0.11 0.07 -0.12 1.00 MR -0.10 -0.19 0.37 -0.11 -0.05 0.02 0.05 0.08 0.01 -0.15 -0.79 1.00 The estimated equation by OLS is GPA=.73 + .44HS + .04A + .01AS - .07S + .02M + .14PC + .01D + .01B + .16F + .08HR - .01MR (.76) (.10) (.03) (.01) (.03) (.06) (.06) (.08) (.06) (.23) (.12) (.10) [1.36] [1.75] [1.32] [1.28] [1.23] [1.11] [1.43] [1.26] [1.47] [4.22] [3.45] Residual (df) =129, TSS=19.41, ESS=14.03. Values in parentheses (under the regression equation) are standard errors and those in square brackets are the variance inflation factors (VIFs). Which 2 pairs of variables are most correlated with the regressand? Which 3 pairs of variables are mostly multicollinear? Identify 3 pairs of variables that are most correlated.

The University Secretary wants to determine how University grade point average, GPA (highest being 4.0) of a sample of students from the University depends on a student’s high school GPA (HS), age of a student (A), achievement test score (AS), average number of lectures skipped each week (S), gender of a student (where M=1 if a student is male or 0 otherwise), computer or PC ownership of a student (where PC=1 if a student owns a computer or 0 otherwise), the means of transport to school (drive, bicycle or walk; where D=1 if a student drives to campus or 0 otherwise, B=1 if a student bicycles to campus or 0 otherwise), and finally, the subject major of the student (finance, human resource, marketing and accounting; where F=1 if a student majors in finance or 0 otherwise, HR=1 if a student majors in human resource or 0 otherwise, MR=1 if a student majors in marketing or 0 otherwise). Use the correlation matrix and dummy regression output to answer the questions. GPA HS A AS S M PC D B F HR MR GPA 1.00 HS 0.41 1.00 A -0.02 -0.26 1.00 AS 0.21 0.35 -0.08 1.00 S -0.26 -0.09 -0.08 0.12 1.00 M -0.08 -0.21 0.04 0.18 0.20 1.00 PC 0.22 0.04 -0.09 0.04 -0.21 -0.07 1.00 D -0.11 -0.19 0.27 -0.20 0.26 -0.08 0.02 1.00 B 0.08 0.14 -0.05 0.16 -0.13 0.13 -0.10 -0.38 1.00 F 0.08 0.12 -0.22 0.18 0.06 0.04 0.08 -0.08 -0.11 1.00 HR 0.08 0.17 -0.49 0.08 0.06 0.05 -0.04 -0.11 0.07 -0.12 1.00 MR -0.10 -0.19 0.37 -0.11 -0.05 0.02 0.05 0.08 0.01 -0.15 -0.79 1.00 The estimated equation by OLS is GPA=.73 + .44HS + .04A + .01AS - .07S + .02M + .14PC + .01D + .01B + .16F + .08HR - .01MR (.76) (.10) (.03) (.01) (.03) (.06) (.06) (.08) (.06) (.23) (.12) (.10) [1.36] [1.75] [1.32] [1.28] [1.23] [1.11] [1.43] [1.26] [1.47] [4.22] [3.45] Residual (df) =129, TSS=19.41, ESS=14.03. Values in parentheses (under the regression equation) are standard errors and those in square brackets are the variance inflation factors (VIFs). Which 2 pairs of variables are most correlated with the regressand? Which 3 pairs of variables are mostly multicollinear? Identify 3 pairs of variables that are most correlated.

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The University Secretary wants to determine how University grade point average, GPA (highest being 4.0) of a sample of students from the University depends on a student’s high school GPA (HS), age of a student (A), achievement test score (AS), average number of lectures skipped each week (S), gender of a student (where M=1 if a student is male or 0 otherwise), computer or PC ownership of a student (where PC=1 if a student owns a computer or 0 otherwise), the means of transport to school (drive, bicycle or walk; where D=1 if a student drives to campus or 0 otherwise, B=1 if a student bicycles to campus or 0 otherwise), and finally, the subject major of the student (finance, human resource, marketing and accounting; where F=1 if a student majors in finance or 0 otherwise, HR=1 if a student majors in human resource or 0 otherwise, MR=1 if a student majors in marketing or 0 otherwise). Use the correlation matrix and dummy regression output to answer the questions.

	GPA	HS	A	AS	S	M	PC	D	B	F	HR	MR
GPA	1.00
HS	0.41	1.00
A	-0.02	-0.26	1.00
AS	0.21	0.35	-0.08	1.00
S	-0.26	-0.09	-0.08	0.12	1.00
M	-0.08	-0.21	0.04	0.18	0.20	1.00
PC	0.22	0.04	-0.09	0.04	-0.21	-0.07	1.00
D	-0.11	-0.19	0.27	-0.20	0.26	-0.08	0.02	1.00
B	0.08	0.14	-0.05	0.16	-0.13	0.13	-0.10	-0.38	1.00
F	0.08	0.12	-0.22	0.18	0.06	0.04	0.08	-0.08	-0.11	1.00
HR	0.08	0.17	-0.49	0.08	0.06	0.05	-0.04	-0.11	0.07	-0.12	1.00
MR	-0.10	-0.19	0.37	-0.11	-0.05	0.02	0.05	0.08	0.01	-0.15	-0.79	1.00

The estimated equation by OLS is

GPA=.73 + .44HS + .04A + .01AS - .07S + .02M + .14PC + .01D + .01B + .16F + .08HR - .01MR

(.76) (.10) (.03) (.01) (.03) (.06) (.06) (.08) (.06) (.23) (.12) (.10)

[1.36] [1.75] [1.32] [1.28] [1.23] [1.11] [1.43] [1.26] [1.47] [4.22] [3.45]

Residual (df) =129, TSS=19.41, ESS=14.03.

Values in parentheses (under the regression equation) are standard errors and those in square brackets are the variance inflation factors (VIFs).

Which 2 pairs of variables are most correlated with the regressand?
Which 3 pairs of variables are mostly multicollinear?
Identify 3 pairs of variables that are most correlated.

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