results-interpretation

# Results Interpretation Skill

## Purpose
Correctly interpret and report statistical findings with appropriate nuance.

## Key Principles

**1. Effect Size > p-value**
- Report effect sizes with 95% CI
- Statistical significance ≠ practical importance

**2. Confidence Intervals**
- Range of plausible values
- Precision of estimate
- If CI includes 0, not statistically significant

**3. P-values**
- Probability of data given H0
- NOT: Probability H0 is true
- NOT: Probability of replication

**4. Multiple Comparisons**
- Adjust alpha if running many tests
- Distinguish primary vs exploratory

## Correct Reporting

**Example:**
"The intervention group showed higher scores (M=45.2, SD=8.3) than control (M=37.8, SD=9.1), t(98)=3.45, p<.001, d=0.69, 95% CI[0.29, 1.09]. This represents a medium-to-large effect."

**Include:**
- Descriptive statistics
- Test statistic and df
- P-value
- Effect size with CI
- Interpretation

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**Version:** 1.0.0