Logistic regression is commonly used in medical and other fields to analyze data. Various statistics are used to evaluate the model's effectiveness, similar to linear regression. Confidence intervals are calculated using different methods. Polytomous logistic regression is a compromise between using continuous or binary data. Tree-based models are an alternative to logistic regression for classification. Diagnostics are crucial in logistic regression, just like in linear regression.