USING R FOR STATISTICS

R is a popular and growing open source statistical analysis and graphics environment as well as a programming language and platform. If you need to use a variety of statistics, thenUsing R for Statistics will get you the answers to most of the problems you are likely to encounter. Using R for Statis [...]
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R is a popular and growing open source statistical analysis and graphics environment as well as a programming language and platform. If you need to use a variety of statistics, thenUsing R for Statistics will get you the answers to most of the problems you are likely to encounter. Using R for Statistics is a problem-solution primer for using R to set up your data, pose your problems and get answers using a wide array of statistical tests. The book walks you through R basics and how to use R to accomplish a wide variety statistical operations. You'll be able to navigate the R system, enter and import data, manipulate datasets, calculate summary statistics, create statistical plots and customize their appearance, perform hypothesis tests such as the t-tests and analyses of variance, and build regression models. Examples are built around actual datasets to simulate real-world solutions, and programming basics are explained to assist those who do not have a development background. After reading and using this guide, you'll be comfortable using and applying R to your specific statistical analyses or hypothesis tests. No prior knowledge of R or of programming is assumed, though you should have some experience with statistics. What you'll learn How to apply statistical concepts using R and some R programmingdata, and combine and restructure datasetHow to summarize continuous and categorical variablesWhat is a probability distributionHow to create and customize plotsHow to do hypothesis testingHow to build and use regression and linear models Who this book is for No prior knowledge of R or of programming is assumed, making this book ideal if you are more accustomed to using point-and-click style statistical packages. You should have some prior experience with statistics, however. Table of Contents 1. R Fundamentals 2. Working with Data Files 3. Preparing and Manipulating Data 4. Combining and Restructuring Data Sets 5. Continuous Variables 6. Tabular Data 7. Probability Distribution 8. Creating Plots 9. Customizing Plots 10. Hypothesis Tests 11. Regression and Linear Models 12. Appendix A: Basic Programming with R 13. Appendix B: Add-on Packages 14: Appendix C: Data Sets "