R Expert

This is a comprehensive R programming reference that covers everything from basic vectors and data frames through tidyverse operations, ggplot2 visualizations, and statistical modeling. You'll reach for it when working with data analysis pipelines, building regression models, or creating publication-ready plots. The examples are practical and production-focused, covering dplyr chains, time series forecasting with ARIMA, and machine learning with caret and randomForest. It includes R Markdown templates for reproducible reports and best practices around vectorization and code style. The statistical analysis section is solid, walking through t-tests, ANOVA, and logistic regression with assumption checking. If you're doing data science work in R, this gives you patterns you can copy and adapt rather than searching Stack Overflow.