The handbook focuses on using statistics to understand relationships between different variables in the medical and pharmaceutical fields. It covers topics such as simple and multiple linear regression, correlation, issues in modeling, and special regression techniques, including logistic regression. The primary aim is to help practitioners and researchers understand how to analyze and interpret data to make informed decisions in clinical and pharmaceutical settings. Key findings include ways to address specific challenges in regression analysis, such as determining variables from outcomes, dealing with patterns in data, and selecting the most suitable models for analysis in different situations.