Statistical Modeling in R with moderndive Regression Functions

Understanding regression analysis can feel overwhelming when you have to manually parse complex model objects. The moderndive package simplifies this process by providing clean, tidy summaries of your regression models. This text-based course guides you through the foundational concepts of linear regression and shows you how to easily extract and interpret your model data. You will start by learning core statistical terminology and the basics of fitting linear models in R. From there, you will discover how to use specialized extraction functions to isolate explanatory variables, fitted values, and residuals for deeper analysis. We also cover modern data practices, including how to integrate these outputs with tidyverse tools for clean visualization and reporting. What you'll learn: - Understand the foundational concepts of linear regression and model fitting in R - Extract regression coefficients and explanatory variables using moderndive functions - Analyze fitted values and residuals to assess model diagnostics and fit - Apply tidy data principles to format regression outputs for downstream analysis - Interpret statistical summaries and hypothesis tests with confidence This course is designed for beginners, data analysts, and students who want a clearer, more intuitive way to work with regression models in R. No advanced mathematical background or prior modeling experience is required, though a basic familiarity with R syntax is helpful. Start reading to simplify your statistical workflows today.