📊 Statistics Calculator Suite

Statistics Toolkit Overview

Fast map from question → correct calculator → minimal interpretation steps.

1. Pick the Right Tool

2. Minimal Decision Flow

1. Define variable type (continuous, discrete, categorical).
2. State objective (describe, compare, predict, proportion, count).
3. Check assumptions (independence, approximate normality, sample size adequacy).
4. Select calculator & input clean data.
5. Report statistic + context (n, units, any exclusions).

3. Parameter Heuristics

• Skewed data? Prefer median & IQR over mean & σ.
• Small n (<30) with unknown σ? Avoid strict normal assumptions; consider t logic.
• Proportions with p near 0/1: use larger n or exact methods.

4. Quality Checks

• Recalculate one value manually to validate pipeline.
• Σ frequencies = n? If not, data parsing issue.
• Outliers: report both with & without if they shift conclusions.

5. Common Pitfalls

• Confusing statistical significance with practical impact.
• Using mean for heavy-tail distributions without caveat.
• Multiple comparisons without adjustment.
• Z‑score use on clearly non‑normal tiny samples.

6. Quick Reference

7. FAQ

• Which center measure? Median for skew/outliers; mean for symmetric; mode for categorical.
• When is n “large”? Often n ≥ 30 for mean CLT; depends on distribution shape.
• Why log transform? Stabilizes variance & normalizes right-skew data.

8. Action Tip

Attach a one-line “assumption statement” (e.g., “Approx symmetric; no extreme outliers; n=48”) to each reported statistic—prevents misinterpretation later.