Statistical Test Result #189 — Analysis Report
Contents
- glm (#189) completed
1. Glm
2026-09-21 02:16:49 · statistical_test
The glm on count completed.
| family | poisson |
|---|---|
| aic | 459.446463 |
| deviance | 93.873857 |
| null_deviance | 689.045915 |
| pseudo_r2 | 0.863763 |
| n_obs | 100 |
| dispersion_phi | 0.926151 |
| deviance_gof_p | 0.599153 |
| method | glm |
| value_col | count |
| significant | True |
coefficients
| term | coef | se | z | p | ci_lower | ci_upper |
|---|---|---|---|---|---|---|
| const | 0.523342 | 0.095226 | 5.495813 | 0.0 | 0.336703 | 0.709981 |
| predictor | 0.292051 | 0.012951 | 22.551123 | 0.0 | 0.266669 | 0.317434 |
coef forest
fitted vs observed
residuals vs fitted
Method & Provenance
- Method
- Count GLM (Poisson / Negative Binomial)
- Engine
- Python · statsmodels 0.14.6
- Input dataset
- gallery — example_glm_counts.csv
- Started
- 2026-09-21 02:16:49.944469
- Permanent link
- https://cat-g-omxpert.wishartlab.com/results/by-token/775627731dca4c13a90b35a39d9a2c5e
| Parameter | Value |
|---|---|
| test_type | glm |
| value_col | count |
| predictor_cols | predictor |
Command history
# python import statsmodels.api as sm # python model = sm.GLM(y_counts, X_predictors, family=sm.families.Poisson()) # python fit = model.fit()