Business Data Analytics with R: Regression Models for Decision Making

Every modern business generates vast amounts of data, but the real value lies in turning that data into actionable strategic decisions. Understanding the relationships between key business variables—such as marketing spend, pricing strategies, and customer retention—is essential for driving organizational growth. This text-based course guides you through the foundational concepts of regression analysis and statistical modeling using the R programming language. You will transition from basic data observation to constructing reliable predictive models that solve actual management problems. What you'll learn: - Understand core statistical concepts and regression terminology before writing any code - Build and interpret linear regression models to analyze complex business relationships - Clean and prepare business datasets using modern R packages and tidy data principles - Evaluate model fit, analyze residuals, and diagnose potential statistical issues - Apply multiple regression techniques to control for confounding variables in business scenarios - Translate statistical outputs into clear, actionable business insights for decision-makers This course begins with essential definitions and the fundamentals of data structures in R, ensuring a solid foundation. From there, you will progress through step-by-step written explanations and code walkthroughs that demonstrate how to build, refine, and validate regression models using realistic business scenarios. Designed for business professionals, managers, and aspiring analysts, this course requires no prior advanced programming or statistical background. Start reading today to unlock the power of predictive business modeling.