Behavioral Research: Statistical Methods
CG3.402Vinoo Alluri•Monsoon 2025-26•4 credits
Answer Structure Templates
University exams reward formatting. Use these.
Define + formula + when to use
- Give 1-line definition.
- State the formula.
- State the assumptions / range / domain.
- Give an example use case.
- Note one common misinterpretation.
Pick-the-test
- Identify DV scale (nominal / ordinal / interval / ratio).
- Identify IV scale and #groups.
- Decide independent vs paired.
- Pick parametric default; check assumptions; drop to nonparametric if violated.
- State the test, df formula, and effect size measure.
Critical evaluation of a study
- IV/DV identification.
- Hypotheses.
- Test recommendation with justification.
- Assumptions check.
- Effect size + CI.
- Discuss limitations + recommendations.
Bayes update (Bayes' rule problem)
- List P(H), P(D|H), P(D|¬H).
- Compute P(D) = P(D|H)·P(H) + P(D|¬H)·P(¬H).
- Apply Bayes: P(H|D) = P(D|H)·P(H) / P(D).
- Compare to the prior — Bayes makes the update explicit.
Hypothesis-test report
- State H₀ and H₁.
- Choose α.
- State test + df.
- Report statistic, p-value, effect size, 95% CI.
- Interpret: statistical AND practical significance.
Multicollinearity diagnosis
- Inspect predictor correlations / VIFs.
- Note VIF > 5–10 = severe.
- Recommend: drop / combine via PCA / ridge / collect more data.
- Caveat: model may still predict well even when coefficients are unstable.
ANOVA analysis plan
- State H₀ and H₁ across the k groups.
- Check assumptions (Levene, Q-Q).
- Report F, df, p, η² / partial η².
- If significant → Tukey HSD post-hoc.
- If RM-ANOVA → Mauchly + Greenhouse-Geisser as needed.
Factor analysis pipeline
- Item screening + reliability (Cronbach's α).
- Sampling adequacy: KMO + Bartlett.
- Choose # factors: parallel analysis > scree > Kaiser.
- EFA → rotation → interpret loadings.
- CFA on held-out sample; report fit indices (CFI, RMSEA, SRMR).