Below is the output from the regression procedure from the statistical package SPSS. Note that the tests of the coefficients use t tests rather than an F test. However, if the t values are squared then the results are identical to those computed in the text. For example, if you square the t of 2.047 for SAT you obtain 4.19 as calculated above. Note that the p values match.

Model Summary

Model

R

R Square

Adjusted R Square

Std. Error of the Estimate

 

1

.789a

.623

.616

.27718

a. Predictors: (Constant), SAT, high_GPA

 

ANOVAb

Model

Sum of Squares

df

Mean Square

F

Sig.

1

Regression

12.961

2

6.481

84.349

.000a

Residual

7.837

102

.077

 

 

Total

20.798

104

 

 

 

a. Predictors: (Constant), SAT, high_GPA

b. Dependent Variable: univ_GPA

 

Coefficientsa

Model

Unstandardized Coefficients

Standardized Coefficients

t

Sig.

B

Std. Error

Beta

1

(Constant)

.540

.318

 

1.699

.092

high_GPA

.541

.084

.625

6.465

.000

SAT

.001

.000

.198

2.047

.043

a. Dependent Variable: univ_GPA