Using R for Statistics

Using R for Statistics will get you the answers to most of the problems you are likely to encounter when using a variety of statistics. This book 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. Noprior knowledge of R or of programming is assumed, though you should have some experience with statistics.

If you need to use a variety of statistics, then Using R for Statistics will get you the answers to most of the problems that are likely to be posed. This book 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.

Autorentext
Sarah Stowell is a Contract Statistician with Mitsubishi Pharma Europe and has been a Statistician with MDSL International and GlaxoSmithKline previously. She holds a Master of Science degree in Statistics.

Klappentext
Using R for Statistics will get you the answers to most of the problems you are likely to encounter when using a variety of statistics. This book 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. Noprior knowledge of R or of programming is assumed, though you should have some experience with statistics.

Inhalt
1. R Fundamentals2. Working with Data Files3. Preparing and Manipulating Data4. Combining and Restructuring Data Sets5. Continuous Variables6. Tabular Data7. Probability Distribution8. Creating Plots9. Customizing Plots10. Hypothesis Tests11. Regression and Linear Models12. Appendix A: Basic Programming with R13. Appendix B: Add-on Packages14: Appendix C: Data Sets

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