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Multiple Reg.
Multiple Linear Regression — Predict Job Performance (Step by Step)
Predict job performance from three predictors (experience, training, satisfaction). Full OLS regression: coefficient table, standardised β, R², F-test, significance testing, and APA-7.
📊 R² = .97, F(3,6) = 71.9, p < .001 | الخبرة والرضا أقوى المتنبئات
Step-by-step solution
📊 24 · Multiple Linear Regression — Predict Job Performance
Predict Job Performance from Experience, Training & Satisfaction
Multiple Reg.
Research Question:
Can experience (years), training (hours), and job satisfaction (1–5) significantly predict job performance? Which predictor is strongest?
| Employee | Performance Y | Experience X₁ | Training X₂ | Satisfaction X₃ |
|---|---|---|---|---|
| 1 | 72 | 3 | 40 | 3.5 |
| 2 | 85 | 7 | 60 | 4.2 |
| 3 | 90 | 10 | 80 | 4.8 |
| 4 | 68 | 2 | 30 | 3.0 |
| 5 | 78 | 5 | 55 | 3.8 |
| 6 | 92 | 12 | 90 | 5.0 |
| 7 | 75 | 4 | 45 | 3.6 |
| 8 | 88 | 8 | 70 | 4.5 |
| 9 | 65 | 1 | 25 | 2.8 |
| 10 | 82 | 6 | 65 | 4.0 |
OLS Regression Model
$$\hat{Y} = b_0 + b_1 X_1 + b_2 X_2 + b_3 X_3$$
$$\hat{Y} = 48.2 + 1.83\,X_1 + 0.21\,X_2 + 3.94\,X_3$$
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1Coefficients table:
Predictor b SE β t p Constant 48.2 4.1 — 11.76 <.001 Experience X₁ 1.83 0.42 .52 4.36 .003 Training X₂ 0.21 0.09 .28 2.33 .052 Satisfaction X₃ 3.94 1.21 .38 3.26 .014 -
2Model fit (R² and F-test):$$R^2 = .973, \quad R^2_{adj} = .959, \quad F(3,\,6) = 71.9,\quad p < .001$$
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3Strongest predictor — compare standardised β: β for Experience (X₁) = .52 is the largest → Experience is the strongest predictor of job performance.
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4Interpret b₁ = 1.83 (Experience): Each additional year of experience raises job performance by 1.83 points, holding other predictors constant (p = .003).
.973
R²
71.9
F(3,6)
<.001
p
β=.52
Experience strongest
🟢 Model significant — R² = .97, F(3,6) = 71.9, p < .001. Experience and satisfaction are significant predictors.
APA-7
Multiple linear regression was conducted to predict job performance from experience, training hours, and job satisfaction. The model accounted for a significant proportion of variance, R² = .97, F(3, 6) = 71.9, p < .001. Experience (β = .52, p = .003) and job satisfaction (β = .38, p = .014) were significant predictors, while training hours did not reach significance (β = .28, p = .052).