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The Question:
For some Mechanical Engineer students, data for 224 student’sGPAs in their first 4 semesters of college were compared usingseveral predictors, namely HSM, HSS, HSE, SATM, and SATV. Heresignificant level ? is 0.05.
Then, the researcher fit a regression model and got thefollowing results (intercept is included in the model):
ANOVA Table
Source | DF | Sum of Squares | Mean Squares | F ratio |
Model(Reg) | (A) | (D) | (E) | (F) |
Error(Residual) | (B) | 105.65 | 0.4846433 | Prob>F |
Total | (C) | 135.46 | | <0.001 |
Parameter Estimates Table
Term | Estimate | Std Error | t Ratio | Prob>|t| |
Intercept | 0.2187920884 | 0.40332538 | 0.54 | 0.5880 |
HSM | 0.1464842907 | 0.03900487 | (G) | 0.0002 |
HSS | 0.0274662163 | 0.03728366 | 0.74 | 0.4621 |
HSE | 0.0770581216 | 0.03929423 | 1.96 | 0.0511 |
SATM | 0.0009273573 | 0.00067983 | 1.36 | 0.1739 |
SATV | .0004012914 | 0.00058484 | -0.69 | 0.4933 |
- What are the values for (A), (B), (C), (D), (E), (F) and(G)?
- State the multiple regression model for this problem.
- What % of the variation in GPA are we explaining by themultiple regression?
- Specify the prediction equation (Include all theregressors)
- Determine if this is a significant model, i.e. check ANOVAtable. (If significant, then p-value < ?.) Here significantlevel ? is 0.05.
- Determine if each predictor variable is significant to themodel, give the reason, based on the JMP output (i.e. compare thetest statistics or p-value)
