Package Description:

This package is designed for students, researchers, analysts, and professionals who want to use statistics and data science to analyze real-world data with confidence. We will work together to understand the statistical ideas that matter most in practice, including distributions, uncertainty, hypothesis testing, regression models, model assumptions, interpretation, visualization, and communicating results clearly. Depending on your goals, we can cover linear regression, logistic regression, generalized linear models, mixed-effects models, classification, model comparison, feature selection, cross-validation, and practical data analysis workflows in Python. The focus is not only on running statistical models, but on understanding what the model is doing, when it is appropriate, how to interpret the results, and how to avoid common mistakes in real research or applied data science projects.