Hệ số tương quan, hồi qui

This study compares Binary Logistic Regression and Multinomial Logistic Regression as two approaches for analyzing categorical data. Binary Logistic Regression is applied when the dependent variable has two categories (e.g., “yes” or “no”), while Multinomial Logistic Regression is suitable for variables with more than two categories (e.g., “low”, “medium”, “high”). The comparison aims to explore the differences in model structure, assumptions, and predictive performance between the two methods across various data contexts. The results are expected to provide a clearer understanding of when each model is most appropriately applied.

Perbedaan Multinomial dan Binary

Covid_19 epidemiology report in North America continent