Books [Winston Chang] Cookbook for R: Best R Programming TIPs

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ОПИСАНИЕ:

The goal of this cookbook is to provide solutions to common tasks and problems in analyzing data. Each recipe tackles a specific problem with a solution you can apply to your own project, and includes a discussion of how and why the recipe works.

Each recipe addresses a specific problem and includes a discussion that explains the solution and provides insight into how it works. If you're a beginner, this book will help get you started. If you're an intermediate user, this book will jog your memory and expand your horizons. You'll get the job done faster and learn more about R in the process.

R is a powerful tool for statistics, graphics, and statistical programming. It is used by tens of thousands of people daily to perform serious statistical analyses. It is a free, open source system whose implementation is the collective accomplishment of many intelligent, hard-working people.

At its core, this is an introductory statistics textbook pitched primarily at psychology students. As such, it covers the standard topics that you'd expect of such a book: study design, descriptive statistics, the theory of hypothesis testing, t-tests, X2 tests, ANOVA and regression.

• Create vectors, handle variables, and perform other basic functions
• Simplify data input and output
• Tackle data structures such as matrices, lists, factors, and data frames
• Work with probability, probability distributions, and random variables
• Calculate statistics and confidence intervals and perform statistical tests
• Create a variety of graphic displays
• Build statistical models with linear regressions and analysis of variance (ANOVA)
• Explore advanced statistical techniques, such as finding clusters in your data

About the Authors:

• WWinston Chang is a software engineer at RStudio, where he works on data visualization and software development tools for R. He has a Ph.D. in Psychology from Northwestern University, and created the Cookbook for R website, which contains recipes for common tasks in R.

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