An Introduction to Data Analysis in R

An Introduction to Data Analysis in R is a practical, classroom-ready textbook for readers who want to learn data analysis through the R language without being thrown in at the deep end. Written by Alfonso Zamora Saiz, Carlos Quesada González, Lluís Hurtado Gil, and Diego Mondéjar Ruiz, it moves steadily from programming basics to the full workflow of preparing, exploring, visualizing, and interpreting data.

A hands-on path from first script to final analysis 💻

The book is built for learners who need a clear route into R and data work. It begins with core programming ideas, data structures, and control flow, then expands into importing and collecting data, preprocessing, visualization, descriptive statistics, inference, and multivariate methods. The result is a guided introduction that keeps the technical pieces connected to real analytical practice.

Coverage that follows the data-analysis workflow

Rather than treating R as a language in isolation, the book places it inside the larger process of analysis. Readers encounter data sources and tabulated file types, web scraping, data tables, base graphics, ggplot2, plotly, leaflet, descriptive measures, confidence intervals, hypothesis tests, correlation, linear models, and categorical variables. That broad structure makes it useful for readers who want to understand not just how to code, but how to move from raw data to conclusions.

Designed for study, teaching, and self-paced review

The text is self-contained and includes exercises across the sections, making it especially suitable for semester courses and structured independent study. Its tone and scope make it a strong fit for students in mathematics, statistics, economics, finance, business, and related fields, as well as professionals who need a solid first book on R for data analysis.

Why it stands out

What makes this title appealing is its balance: it is technical enough to be serious, but approachable enough to serve as an entry point. The combination of coding, visualization, and statistical reasoning gives the book a practical edge that readers can apply immediately.