R All-in-One For Dummies

A deep dive into the programming language of choice for statistics and data

With R All-in-One For Dummies, you get five mini-books in one, offering a complete and thorough resource on the R programming language and a road map for making sense of the sea of data we're all swimming in. Maybe you're pursuing a career in data science, maybe you're looking to infuse a little statistics know-how into your existing career, or maybe you're just R-curious. This book has your back. Along with providing an overview of coding in R and how to work with the language, this book delves into the types of projects and applications R programmers tend to tackle the most. You'll find coverage of statistical analysis, machine learning, and data management with R.

• Grasp the basics of the R programming language and write your first lines of code
• Understand how R programmers use code to analyze data and perform statistical analysis
• Use R to create data visualizations and machine learning programs
• Work through sample projects to hone your R coding skill

This is an excellent all-in-one resource for beginning coders who'd like to move into the data space by knowing more about R.

Introduction 1

Book 1: Introducing R 5

Chapter 1: R: What It Does and How It Does It 7

Chapter 2: Working with Packages, Importing, and Exporting 37

Book 2: Describing Data 51

Chapter 1: Getting Graphic 53

Chapter 2: Finding Your Center 93

Chapter 3: Deviating from the Average 103

Chapter 4: Meeting Standards and Standings 113

Chapter 5: Summarizing It All 125

Chapter 6: What’s Normal? 145

Book 3: Analyzing Data 163

Chapter 1: The Confidence Game: Estimation 165

Chapter 2: One-Sample Hypothesis Testing 181

Chapter 3: Two-Sample Hypothesis Testing 207

Chapter 4: Testing More than Two Samples 233

Chapter 5: More Complicated Testing 257

Chapter 6: Regression: Linear, Multiple, and the General Linear Model 279

Chapter 7: Correlation: The Rise and Fall of Relationships 315

Chapter 8: Curvilinear Regression: When Relationships Get Complicated 335

Chapter 9: In Due Time 359

Chapter 10: Non-Parametric Statistics 371

Chapter 11: Introducing Probability 393

Chapter 12: Probability Meets Regression: Logistic Regression 415

Book 4: Learning from Data 423

Chapter 1: Tools and Data for Machine Learning Projects 425

Chapter 2: Decisions, Decisions, Decisions 449

Chapter 3: Into the Forest, Randomly 467

Chapter 4: Support Your Local Vector 483

Chapter 5: K-Means Clustering 503

Chapter 6: Neural Networks 519

Chapter 7: Exploring Marketing 537

Chapter 8: From the City That Never Sleeps 557

Book 5: Harnessing R: Some Projects to Keep You Busy 573

Chapter 1: Working with a Browser 575

Chapter 2: Dashboards — How Dashing! 603

Index 639

Joseph Schmuller is a cognitive scientist and statistical analyst. His recent work in the For Dummies series includes the 5th edition of Statistical Analysis with Excel For Dummies along with Statistical Analysis with R For Dummies and R Projects For Dummies.

Crunch any number of numbers with R

When there’s data about, R is the coding language of choice. This book helps you take charge of your data with the R programming language so you can build datasets, automate data analysis and machine learning tasks, and create visual outputs to communicate your findings. Even if you’re new to programming, these simple instructions will get you started handling tasks usually reserved for data scientists. Find distributions and averages, test statistical hypotheses, create decision trees and neural networks, and put the answers you find into helpful dashboards and visualizations. And do it all the easy way, with this easy-to-understand guide.

5 Mini-Books Inside…

• Introducing R
• Describing Data
• Analyzing Data
• Learning From Data
• Harnessing R: Some Projects to Keep You Busy