Data Visualization with Boxplots in R

Visualizing data distributions is a foundational step in any statistical analysis, yet many struggle to properly read and construct the charts that reveal these patterns. This text-based course guides you through the mechanics of boxplots, helping you decode quartiles, medians, and outliers with confidence. You will transition from understanding core statistical concepts to writing clean, reproducible R code that generates professional plots. What you'll learn: Understand the five-number summary and how it translates to a visual boxplot; Identify and interpret outliers, skewness, and spread in diverse datasets; Create basic boxplots using standard R base graphics; Build highly customizable, publication-ready visualizations using the ggplot2 library; Apply modern data-cleaning workflows to prepare raw variables for plotting; Practice formatting axes, labels, and color palettes to improve plot readability. You will begin by mastering essential statistical definitions before moving on to step-by-step code implementations in R, utilizing tidyverse principles to keep your scripts clean and modern. This course is designed specifically for beginners with no prior programming or advanced statistical experience. Start reading today to transform raw numbers into clear, visual data insights.