This venn diagram illustrates the concept of two events, A and B, within a sample space. The overlapping region represents outcomes that belong to both A and B. This is useful in understanding compound probailities. Common in set-based probability problems and useful when analyzing joint vs independent events in statistics.

This post explores how to use boxplots in R to visually compare the distribution of diamond prices across different quality grades(cut) using the ggplot2::diamonds dataset. Boxplots provide a quick, informative view of central tendency, spread, and outliers, helping identify patterns in pricing based on diamond cut. This visualization is a key part of exploratory data analysis and forms the basis for more advanced statistical modeling.

This entry focuses on how to use the boxplot() function in base R to compare multiple groups. It covers customizations like color, labels, and adding references lines, making it easy to summarize and contrast data distributions.

This post explores the creation and customization of histograms in base R using the hist() function. It shows how to visualize distributions, control bin widths, add color, and highlight summary statistics like the mean using abline().

This post demonstrates the use of the plot() function in base R for creating scatter plots and line graphs. It includes customizations for point style, color, regression lines, and annotations, offering a clean approach to visualizing variable relationships without additional libraries.