Geographic Retail Sales Analysis with R

Does physical location actually drive retail performance, or is it just noise? For retail analysts and business planners, understanding the spatial factors behind sales data is crucial for making smart expansion and marketing decisions. This text-based course guides you through the process of evaluating geographic retail performance using statistical analysis. You will start with the fundamental concepts of spatial data and statistical testing before moving into hands-on analysis. By the end of this course, you will be able to confidently import, clean, and analyze retail sales datasets to discover geographic trends. What you'll learn: Understand the core principles of spatial data and how location influences consumer behavior; Clean and prepare messy retail datasets using modern tidyverse tools in R; Perform exploratory data analysis to identify regional sales patterns and anomalies; Apply statistical tests such as ANOVA and regression to measure the impact of location on revenue; Interpret statistical outputs to make data-driven recommendations for store placement. We begin with essential definitions and statistical terminology, then walk through a practical retail case study using structured code explanations and clear analysis steps. This course is designed for beginners, business analysts, and aspiring data professionals who want to learn R for spatial business analysis. Start making smarter, data-backed retail decisions today.