Quantitative Analysis
by poemswe
You must use this when selecting statistical tests, interpreting effect sizes, or conducting power analysis.
Skill Details
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name: quantitative-analysis description: You must use this when selecting statistical tests, interpreting effect sizes, or conducting power analysis. tools:
- WebSearch
- WebFetch
- Read
- Grep
- Glob
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.
<output_format>
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.] </output_format>
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