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Some of the Book contents

• Statistical Models in R
• Defining Statistical Models; Formulae
• Contrasts
• Linear Models
• Generic Functions for Extracting Model Information
• Analysis of Variance and Model Comparison
• ANOVA Tables
• Updating Fitted Models
• Generalized Linear Models
• Families
• The glm() Function
• Nonlinear Least Squares and Maximum Likelihood Models
• Least Squares
• Maximum Likelihood
• Some Non-Standard Models
• Graphical Procedures
• High-Level Plotting Commands
• The plot() Function
• Displaying Multivariate Data
• Display Graphics
• Arguments to High-Level Plotting Functions
• Low-Level Plotting Commands
• Mathematical Annotation
• Hershey Vector Fonts
• Interacting with Graphics
• Using Graphics Parameters
• Permanent Changes: The par() Function
• Temporary Changes: Arguments to Graphics Functions
• Graphics Parameters List
• Graphical Elements
• Axes and Tick Marks
• Figure Margins
• Multiple Figure Environment
• Device Drivers
• PostScript Diagrams for Typeset Documents
• Multiple Graphics Devices
• Dynamic Graphics
• Packages
• Standard Packages
• Contributed Packages and CRAN
• Namespaces
• OS Facilities
• Files and Directories
• Filepaths
• System Commands
• Compression and Archives

Book Description

This introduction to R is derived from an original set of notes describing the S and S-Plus environments written in 1990–2 by Bill Venables and David M. Smith when at the University of Adelaide.

Authors have made a number of small changes to reflect differences between the R and S programs, and expanded some of the material..

Book Overview

This isn’t just another dry technical manual. The R Manuals walk you through the core concepts of the R programming language with a conversational tone that keeps things light and engaging. You’ll get step-by-step instructions on data manipulation, statistical analysis, and even some cool data visualization tricks. There’s also a handy section on troubleshooting common errorsbecause let’s be honest, we all run into them! Each chapter is packed with real-world examples that show you how to apply what you’re learning right away.

Why Read This Book

Let’s face it: learning a new programming language can be daunting. But The R Manuals make it feel like you’ve got a coding buddy by your side. The explanations are clear without being condescending, and there’s just enough humor to keep things interesting (who said code can’t be fun?). If you’ve ever felt overwhelmed by technical jargon or endless online tutorials, this book cuts through the noise and gives you exactly what you need to knowno more, no less. Whether you want to analyze data for work or just impress your friends with some sweet charts, this book has your back.

Who This Book Is For

Are you a student tackling your first statistics course? Or maybe a professional looking to add another tool to your data science toolkit? The R Manuals are perfect for anyone who wants to learn R in a way that actually sticks. Even if you’re totally new to programming, the step-by-step approach will help you build skills from the ground up. And if you’re already familiar with other languages but want to see what makes R specialwell, get ready for some pleasant surprises!

What You Will Learn

• The basics of R syntax and structure
• How to import, clean, and manipulate data
• Statistical analysis techniques using R
• Creating stunning data visualizations
• Troubleshooting tips for common coding pitfalls
• Best practices for writing efficient, readable code

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