

Paul Teetor is a quantitative developer with Masters degrees in statistics and computer science.
Meer over Paul TeetorR Cookbook
Proven Recipes for Data Analysis, Statistics, and Graphics
Paperback Engels 2019 2e druk 9781492040682Samenvatting
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
Specificaties
Lezersrecensies
Inhoudsopgave
The Recipes
A Note on Terminology
Software and Platform Notes
Other Resources
Conventions Used in This Book
Using Code Examples
O’Reilly Online Learning
How to Contact Us
Acknowledgments
1. Getting Started and Getting Help
2. Some Basics
3. Navigating the Software
4. Input and Output
5. Data Structures
6. Data Transformations
7. Strings and Dates
8. Probability
9. General Statistics
10. Graphics
11. Linear Regression and ANOVA
12. Useful Tricks
13. Beyond Basic Numerics and Statistics
14. Time Series Analysis
15. Simple Programming
Index
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