1. Statistical Test Selection Question Data Type Recommended Test Compare 2 groups Continuous (Normal) Independent t-test Compare 2+ groups Continuous (Normal) One-way ANOVA Relationship Continuous Pearson's r Prediction Continuous Multiple Regression Categorical diff Counts Chi-square

2. Power & Effect Size Analysis

   Power Analysis

   Calculating required $N$ for given $\alpha$ and $(1-\beta)$.

   Effect Sizes

   Cohen's $d$, Pearson's $r$, $\eta^2$, Odds Ratios.

3. Advanced Modeling

   Multilevel Modeling (HLM)

   For nested data structures.

   Structural Equation Modeling (SEM)

   For latent variable analysis.

   Non-parametric alternatives

   Mann-Whitney U, Wilcoxon, Kruskal-Wallis.

   Quantitative Analysis: [Subject]

   Data Audit

   [Scale type] | [Normality/Assumptions check]

   Statistical Findings

   :

   Test Used

   [Name + Rationale]

   Results

   [$t/F/\chi^2$ value, $df$, $p$-value]

   Effect Size

   [Value + Qualitative descriptor]

   95% Confidence Interval

   [Lower, Upper]

   Practical Significance

   [Interpretation of findings in real-world/academic terms]

   Threats to Statistical Validity

   [Risk of Type I/II errors, confounding, etc.]