Chi-Square Goodness-of-Fit Lab
Categorical Inference
1-Variable Multinomial
Evaluate whether observed category counts follow a hypothesized equal split or custom market benchmarks, and pinpoint which categories drive the discrepancy.
Case Study Scenario
Chi-Square (χ²)
—
Sum of squared residuals / E
Degrees of Freedom
—
k - 1 categories
p-Value
—
P(χ² ≥ observed | H₀)
Primary Driver
—
Largest component share
Total Sample (N)
—
Sum of observed counts
Observed (Blue) vs. Expected (Gray) Frequencies
■ Observed Count (\(O\))
■ Expected Count (\(E\))
Category Frequency & Component Calculations
| Category Name | Observed (\(O\)) | Hypothesized % | Expected (\(E\)) | Residual (\(O - E\)) | Component (\(\frac{(O-E)^2}{E}\)) |
|---|
Edit observed counts directly in table to see results update live.