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Learning R Programming

You're reading from  Learning R Programming

Product type Book
Published in Oct 2016
Publisher Packt
ISBN-13 9781785889776
Pages 582 pages
Edition 1st Edition
Languages
Author (1):
Kun Ren Kun Ren
Profile icon Kun Ren

Table of Contents (21) Chapters

Learning R Programming
Credits
About the Author
About the Reviewer
www.PacktPub.com
Preface
1. Quick Start 2. Basic Objects 3. Managing Your Workspace 4. Basic Expressions 5. Working with Basic Objects 6. Working with Strings 7. Working with Data 8. Inside R 9. Metaprogramming 10. Object-Oriented Programming 11. Working with Databases 12. Data Manipulation 13. High-Performance Computing 14. Web Scraping 15. Boosting Productivity

Using statistical functions


R is highly productive in doing statistical computing and modeling since it provides a good variety of functions ranging from random sampling to statistical testing. The functions in the same category share a common interface. In this section, I will demonstrate a number of examples so that you can draw inferences about the usage of other similar functions.

Sampling from a vector

In statistics, the study of a population often begins with a random sample of it. The sample() function is designed for drawing a random sample from a given vector or list. In default, sample() draws a sample without replacement. For example, the following code draws a sample of five from a numeric vector without replacement:

sample(1:6, size = 5)
## [1] 2 6 3 1 4 

With replace = TRUE, the sampling is done with replacement:

sample(1:6, size = 5, replace = TRUE)
## [1] 3 5 3 4 2 

Although sample() is often used to draw samples from a numeric vector, it also works with other...

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