1.2 KiB
1.2 KiB
name, description, allowed-tools, version
| name | description | allowed-tools | version |
|---|---|---|---|
| results-interpretation | Interpret statistical results correctly and comprehensively. Use when: (1) Writing results sections, (2) Discussing findings, (3) Avoiding common misinterpretations, (4) Reporting effect sizes and confidence intervals. | Read, Write | 1.0.0 |
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
Version: 1.0.0