9781492040682-1492040681-R Cookbook: Proven Recipes for Data Analysis, Statistics, and Graphics

R Cookbook: Proven Recipes for Data Analysis, Statistics, and Graphics

ISBN-13: 9781492040682
ISBN-10: 1492040681
Edition: 2
Author: JD Long, Paul Teetor
Publication date: 2019
Publisher: O'Reilly Media
Format: Paperback 598 pages
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Book details

ISBN-13: 9781492040682
ISBN-10: 1492040681
Edition: 2
Author: JD Long, Paul Teetor
Publication date: 2019
Publisher: O'Reilly Media
Format: Paperback 598 pages

Summary

R Cookbook: Proven Recipes for Data Analysis, Statistics, and Graphics (ISBN-13: 9781492040682 and ISBN-10: 1492040681), written by authors JD Long, Paul Teetor, was published by O'Reilly Media in 2019. With an overall rating of 4.4 stars, it's a notable title among other Data Modeling & Design (Databases & Big Data, Mathematical & Statistical, Software, Bioinformatics, Biological Sciences, Mathematical Analysis, Mathematics) books. You can easily purchase or rent R Cookbook: Proven Recipes for Data Analysis, Statistics, and Graphics (Paperback, Used) from BooksRun, along with many other new and used Data Modeling & Design books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $14.77.

Description

Perform data analysis with R quickly and efficiently with more than 275 practical recipes in this expanded second edition. The R language provides everything you need to do statistical work, but its structure can be difficult to master. These task-oriented recipes make you productive with R immediately. Solutions range from basic tasks to input and output, general statistics, graphics, and linear regression.

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, R Cookbook 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.

  • Create vectors, handle variables, and perform 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
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