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SPSS Guide
How to Read SPSS Regression Output
Learn to read the SPSS multiple regression Model Summary, ANOVA, and Coefficients tables: R², F-test, unstandardized B vs. standardized beta, and how to compare predictors' relative importance.
📊 R² = .733, F(2,27) = 37.03, p < .001
Step-by-step solution
💻 37 · How to Read SPSS Regression Output
Interpreting the SPSS Multiple Regression Coefficients Table
SPSS Guide
Research Question:
A researcher predicted salary (in $1000s) from years of experience and years of education for 30 employees. SPSS produced a Model Summary, an ANOVA table, and a Coefficients table. How do you read them, and what do you report?
| Model | B | Std. Error | Standardized β | t | Sig. |
|---|---|---|---|---|---|
| (Constant) | 15.20 | 4.10 | 3.71 | .001 | |
| Experience (yrs) | 1.85 | 0.32 | .612 | 5.78 | <.001 |
| Education (yrs) | 2.10 | 0.68 | .331 | 3.09 | .005 |
Model Summary: R = .856, R² = .733, Adjusted R² = .713 | ANOVA: F(2, 27) = 37.03, p < .001
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1Step 1 — Check the ANOVA row first (is the model useful at all?): F(2, 27) = 37.03, p < .001. The model as a whole significantly predicts salary — safe to move on to individual coefficients.
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2Step 2 — Read R² (how much variance is explained): R² = .733 → experience and education together explain 73.3% of the variance in salary. Report the Adjusted R² (.713) in write-ups with more than one predictor, since R² alone is inflated by adding predictors.
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3Step 3 — Read each predictor's B, t, and Sig.: Both predictors are significant (both Sig. < .05). B = 1.85 for Experience means each extra year of experience predicts a $1,850 salary increase, holding education constant.
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4Step 4 — Use standardized β to compare predictors' relative importance: B can't be compared across predictors measured in different units (years vs. years is fine here, but generally isn't). Standardized β can: Experience (β=.612) has a larger relative effect than Education (β=.331).
.733
R²
37.03
F(2,27)
<.001
p
β=.612
Experience strongest
🔴 Model significant — R² = .733, F(2,27) = 37.03, p < .001. Both experience and education are significant predictors of salary.
APA-7
A multiple linear regression was conducted to predict salary from years of experience and years of education. The model significantly predicted salary, F(2, 27) = 37.03, p < .001, R² = .733 (adjusted R² = .713). Both experience (β = .612, p < .001) and education (β = .331, p = .005) were significant positive predictors.