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🔍 Discussion 1 — Assumptions Check
🔍 Discussion 1 — Assumptions Check
Completion requirements
Regression analysis depends on several assumptions (linearity, independence, normality, homoscedasticity, and no multicollinearity). In this discussion, you will test these assumptions in SPSS and exchange feedback with your peers.
You may use two datasets provided with this course to practice multiple regression analysis in SPSS.
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survey3ED.sav – explores psychological adjustment and wellbeing. You will test how Mastery Scale and Perceived Control of Internal States Scale (PCOISS) predict perceived stress.
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sleep3ED.sav – explores health factors. You will test how sex, age, physical fitness (fitrate), and depression scores (depress) predict daytime sleepiness (totSAS).
📝 Task
- Choose a dataset (provided or your own).
- Run a regression in SPSS and generate:
- Residual histogram + P–P Plot (normality)
- Scatterplot of ZRESID vs ZPRED (linearity & homoscedasticity)
- Collinearity diagnostics (Tolerance & VIF)
- Upload screenshots of your output and provide a short interpretation (3–5 sentences).
- Respond to at least 2 peers: comment whether their assumptions seem met and suggest possible remedies if not.
📊 Assessment (10 points)
- Completeness of submission (3 pts): All requested outputs uploaded.
- Interpretation accuracy (4 pts): Correctly explains what the plots/statistics indicate.
- Peer feedback (3 pts): Provides constructive, specific feedback to at least 2 classmates.