Interpret Logistic Regression Coefficients and Translate Them Into Business Insights

You are a statistical modeling expert who excels at translating quantitative results into clear business narratives. Help me interpret the results of my logistic regression model. **Model Context:** - Dependent variable: [TARGET_VARIABLE_AND_WHAT_IT_REPRESENTS] - Positive class meaning: [WHAT_CLASS_1_REPRESENTS] - Domain: [BUSINESS_DOMAIN] - Sample size: [N_SAMPLES] - Model purpose: [PREDICTION/INFERENCE/BOTH] **Model Output:** ``` [PASTE_MODEL_SUMMARY_WITH_COEFFICIENTS_SE_PVALUES_CI] ``` **Preprocessing Notes:** - Scaled features: [LIST_SCALED_FEATURES_AND_METHOD] - Encoded categoricals: [LIST_CATEGORICAL_FEATURES_AND_ENCODING] - Reference categories: [LIST_REFERENCE_LEVELS_FOR_EACH_CATEGORICAL] Please provide: 1. **Coefficient Interpretation**: For each significant predictor, convert the log-odds coefficient to an odds ratio and explain its meaning in one plain-English sentence. For example: 'A one-unit increase in [feature] is associated with a [X]% increase/decrease in the odds of [target event], holding all other variables constant.' 2. **Statistical Significance Assessment**: Identify which features are statistically significant at the 0.05 and 0.01 levels. Discuss any features that are borderline and what that implies. 3. **Effect Size Ranking**: Rank the features by practical importance (not just p-value). Discuss the difference between statistical significance and practical significance. 4. **Categorical Variable Interpretation**: Explain how to interpret coefficients for dummy-coded variables relative to the reference category. 5. **Model Diagnostics**: Comment on potential multicollinearity, model fit (pseudo R², log-likelihood), and whether the sample size is adequate for the number of predictors. 6. **Executive Summary**: Write a 3-4 sentence non-technical summary of the key findings suitable for a business stakeholder presentation.