# Regression Statistics: Entrance Scores and GPA

Given the Excel output below of x = entrance scores achieved by students and y = GPA

SUMMARY OUTPUT

Regression Statistics

Multiple R 0.883582

R Square 0.780718

Adjusted R Square 0.76385

Standard Error 0.194761

Observations 15

ANOVA

df SS MS F Significance F

Regression 1 1.755647 1.755647 46.28433 1.26E-05

Residual 13 0.493113 0.037932

Total 14 2.24876

Coefficients Standard Error t Stat P-value Lower 95%

Intercept 0.721777 0.351133 2.055565 0.060486 -0.0368

X Variable 0.105546 0.015514 6.803259 1.26E-05 0.07203

Upper 95% Lower 95.000% Upper 95.000%

Intercept 1.480353 -0.0368 1.480353015

X Variable 0.139062 0.07203 0.139061614

Is this model appropriate for regression analysis or more information is needed before you can decide?

a) Yes

b) No

c) More information needed

The slope of the equation line is:

a) .7218

b) .1391

c) .1055

Doing a hypothesis test on whether the slope is = 0, we get:

a) Yes, slope = 0

b) No, slope is not = 0

c) Not enough information to tell one way or the other.

The prediction of student's GPA given the student's entrance score was 27 gives:

a) Not enough information to do this prediction.

b) The student's GPA is predicted to be 3.24

c) The student's GPA is predicted to be 3.57

If this student has achieved one mark higher on the entrance exam, what would your prediction be for his/her GPA?

a) Not enough information to do this prediction.

b) The student's GPA would increase to 3.68.

c) The student's GPA would not increase.

https://brainmass.com/statistics/regression-analysis/regression-statistics-entrance-scores-gpa-511844

#### Solution Preview

Is this model appropriate for regression analysis or more information is needed before you can decide?

a) Yes

The slope of the ...

#### Solution Summary

The following posting helps with problems involving regression statistics.