R Cookbook: Proven Recipes for Data Analysis, Statistics, and Graphics, 2 edition

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R Cookbook: Proven Recipes for Data Analysis, Statistics, and Graphics, 2 edition
EPUB
  • eBook:
    R Cookbook: Proven Recipes for Data Analysis, Statistics, and Graphics, 2 edition
  • Author:
    JD Long, Paul Teetor
  • Edition:
    2 edition
  • Categories:
  • Data:
    July 5, 2019
  • ISBN:
    1492040681
  • ISBN-13:
    9781492040682
  • Language:
    English
  • Pages:
    600 pages
  • Format:
    EPUB

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Book 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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Content

Chapter 1. Getting Started and Getting Help
Chapter 2. Some Basics
Chapter 3. Navigating the Software
Chapter 4. Input and Output
Chapter 5. Data Structures
Chapter 6. Data Transformations
Chapter 7. Strings and Dates
Chapter 8. Probability
Chapter 9. General Statistics
Chapter 10. Graphics
Chapter 11. Linear Regression and ANOVA
Chapter 12. Useful Tricks
Chapter 13. Beyond Basic Numerics and Statistics
Chapter 14. Time Series Analysis
Chapter 15. Simple Programming
Chapter 16. R Markdown and Publishing

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