# SPSS Printout for Regression

Regression

(I have provided additional information about regression for those who are interested. This is not required material for EPSY 5601)

SPSS Printout

Variables Entered/Removed

 Model Variables Entered Variables Removed Method 1 Educational level (years) . Stepwise (Criteria: Probability-of-F-to-enter <= .050, Probability-of-F-to-remove >= .100). 2 Gender . Stepwise (Criteria: Probability-of-F-to-enter <= .050, Probability-of-F-to-remove >= .100). 3 Previous experience (months) . Stepwise (Criteria: Probability-of-F-to-enter <= .050, Probability-of-F-to-remove >= .100).

a Dependent Variable: Beginning salary

Model Summary

 R R Square Adjusted R Square Std. Error of the Estimate Change Statistics Model R Square Change F Change df1 df2 Sig. F Change 1 .633 .401 .400 \$6,098.26 .401 315.897 1 472 .000 2 .680 .462 .460 \$5,784.26 .061 53.637 1 471 .000 3 .696 .484 .481 \$5,671.16 .022 19.974 1 470 .000

a Predictors: (Constant), Educational level (years)

b Predictors: (Constant), Educational level (years), Gender

c Predictors: (Constant), Educational level (years), Gender, Previous experience (months)

ANOVA

 Model Sum of Squares df Mean Square F Sig. 1 Regression 11747808912.317 1 11747808912.317 315.897 .000 Residual 17553096053.137 472 37188762.824 Total 29300904965.454 473 2 Regression 13542369102.880 2 6771184551.440 202.381 .000 Residual 15758535862.574 471 33457613.296 Total 29300904965.454 473 3 Regression 14184764846.649 3 4728254948.883 147.014 .000 Residual 15116140118.804 470 32162000.253 Total 29300904965.454 473

a Predictors: (Constant), Educational level (years)

b Predictors: (Constant), Educational level (years), Gender

c Predictors: (Constant), Educational level (years), Gender, Previous experience (months)

d Dependent Variable: Beginning salary

Coefficients

 Unstandardized Coefficients Standardized Coefficients t Sig. Model B Std. Error Beta 1 (Constant) -6290.967 1340.920 -4.692 .000 Educational level (years) 1727.528 97.197 .633 17.773 .000 2 (Constant) -5096.451 1282.290 -3.974 .000 Educational level (years) 1470.321 98.655 .539 14.904 .000 Gender 4180.769 570.853 .265 7.324 .000 3 (Constant) -7938.049 1408.851 -5.634 .000 Educational level (years) 1625.292 102.753 .596 15.817 .000 Gender 3446.504 583.307 .218 5.909 .000 Previous experience (months) 12.001 2.685 .159 4.469 .000

a Dependent Variable: Beginning salary

Excluded Variables

 Beta In t Sig. Partial Correlation Collinearity Statistics Model Tolerance 1 Gender .265 7.324 .000 .320 .873 Previous experience (months) .219 6.174 .000 .274 .936 2 Previous experience (months) .159 4.469 .000 .202 .862

a Predictors in the Model: (Constant), Educational level (years)

b Predictors in the Model: (Constant), Educational level (years), Gender

c Dependent Variable: Beginning salary

Interpretation of Printout:

Table 1

Summary of Stepwise Regression Analysis for Variables

Predicting Salary (N = 473)

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Variable               B         SE B        b

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Step 1

Education Level      1727.53     97.20     .63***

Step 2

Education Level      1470.32      98.66     .54***

Gender                4180.77     570.85     .27***

Step 3

Education Level      1625.29    102.75     .60***

Gender               3446.50     583.31     .22***

Experience             12.00       2.69     .16***

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Note. R2 = .40 for Step 1; DR2 = .06 for Step 2;

DR2 = .02 for Step 3 (ps < .001).

***p < .001.

Forty-nine percent of the variation in beginning salary can be predicted from an employee’s educational level, gender, and previous experience.

Education level (b = .60) is the best predictor of beginning salary. It accounts for 40% (R2)of the variation in salary from one individual to another.

Education level, gender, and previous experience are statistically significant predictors.

The unstandardized regression equation is:  y = -7938.05 + 1625.29 (years of education) + 3446.50 (gender) + 12.00 (months of previous experience)

The statistical significance of the model is F (3, 470) = 147.01, p < .001.

The best estimate of a beginning salary for a male (1) with 15 years of education and 150 months of experience would be  -7938.05 + 1625.29 (15) + 3446.50 (1) + 12.00 (150) = \$21,687.80