Textbook in PDF format Simplify stats and learn how to graph, analyze, and interpret data the easy way. Statistical Analysis with R For Dummies makes stats approachable by combining clear explanations with practical applications. You'll learn how to download and use R and RStudio—two free, open-source tools—to learn statistics concepts, create graphs, test hypotheses, and draw meaningful conclusions. Get started by learning the basics of statistics and R, calculate descriptive statistics, and use inferential statistics to test hypotheses. Then, visualize it all with graphs and charts. This Dummies guide is your well-marked path to sailing through statistics. Developed specifically for statistical analysis, R is a computer language that implements many of the analytical tools statisticians have developed for decision-making. I wrote this book to show you how to use these tools in your work. R is a computer language — it’s a tool for doing the computation and number-crunching that set the stage for statistical analysis and decision-making. An important aspect of statistical analysis is to present the results in a comprehensible way. For this reason, graphics is a major component of R. Ross Ihaka and Robert Gentleman developed R in the 1990s at the University of Auckland, New Zealand. Supported by the Foundation for Statistical Computing, R is one of the most popular computer languages. RStudio is an open-source integrated development environment (IDE) for creating and running R code. It’s available in versions for Windows, Mac, and Linux. Although you don’t need an IDE in order to work with R, RStudio makes life much easier. Get clear explanations of the basics of statistics and data analysis Learn how to analyze and visualize data with R, step by step Create charts, graphs, and summaries to interpret results Explore hypothesis testing, and prediction techniques This is the perfect introduction to R for students, professionals, and the stat-curious. Introduction Part 1: Getting Started with Statistical Analysis with R Chapter 1: Data, Statistics, and Decisions Chapter 2: R: What It Does and How It Does It Part 2: Describing Data Chapter 3: Getting Graphic Chapter 4: Finding Your Center Chapter 5: Deviating from the Average Chapter 6: Meeting Standards and Standings Chapter 7: Summarizing It All Chapter 8: What’s Normal? Part 3: Drawing Conclusions from Data Chapter 9: The Confidence Game: Estimation Chapter 10: One-Sample Hypothesis Testing Chapter 11: Two-Sample Hypothesis Testing Chapter 12: Testing More than Two Samples Chapter 13: More Complicated Testing Chapter 14: Regression: Linear, Multiple, and the General Linear Model Chapter 15: Correlation: The Rise and Fall of Relationships Chapter 16: Curvilinear Regression: When Relationships Get Complicated Part 4: Working with Probability Chapter 17: Introducing Probability Chapter 18: Introducing Modeling Chapter 19: Probability Meets Regression: Logistic Regression Chapter 21: Ten Valuable Online R Resources