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results-interpretation

@astoreyai/ai_scientist
2
0

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.

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SKILL.md

name results-interpretation
description 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.
allowed-tools Read, Write
version 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