Beginning R: An Introduction to Statistical Programming + code

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Название:Beginning R. An Introduction to Statistical Programming

Автор Dr. Joshua F. Wiley , Larry A. Pace

Издательство: APRESS

Год: 2015

Страниц:356

Язык: English

Формат: pdf

Размер: 9 Mb

Beginning R, Second Edition is a hands-on book showing how to use the R language, write and save R scripts, read in data files, and write custom statistical functions as well as use built in functions. This book shows the use of R in specific cases such as one-way ANOVA analysis, linear and logistic regression, data visualization, parallel processing, bootstrapping, and more. It takes a hands-on, example-based approach incorporating best practices with clear explanations of the statistics being done. It has been completely re-written since the first edition to make use of the latest packages and features in R version 3.

R is a powerful open-source language and programming environment for statistics and has become the de facto standard for doing, teaching, and learning computational statistics. R is both an object-oriented language and a functional language that is easy to learn, easy to use, and completely free. A large community of dedicated R users and programmers provides an excellent source of R code, functions, and data sets, with a constantly evolving ecosystem of packages providing new functionality for data analysis. R has also become popular in commercial use at companies such as Microsoft, Google, and Oracle. Your investment in learning R is sure to pay off in the long term as R continues to grow into the go to language for data analysis and research.

What you’ll learn

How to acquire and install R

Hot to import and export data and scripts

How to analyze data and generate graphics

How to program in R to write custom functions

Hot to use R for interactive statistical explorations

How to conduct bootstrapping and other advanced techniques

Who this book is for

Beginning R, Second Edition is an easy-to-read book that serves as an instruction manual and reference for working professionals, professors, and students who want to learn and use R for basic statistics. It is the perfect book for anyone needing a free, capable, and powerful tool for exploring statistics and automating their use.

Table of Contents

Part I. Learning the R Language

1. Getting Started

2. Dealing with Dates, Strings, and Data Frames

3. Input and Output

4. Control Structures

Part II. Using R for Descriptive Statistics

5. Functional Programming

6. Probability Distributions

7. Working with Tables

Part III. Using R for Inferential Statistics

8. Descriptive Statistics and Exploratory Data Analysis

9. Working with Graphics

10. Traditional Statistical Methods

11. Modern Statistical Methods

12. Analysis of Variance

13. Correlation and Regression

14. Multiple Regression

15. Logistic Regression

16. Modern Statistical Methods II

Part IV. Taking R to the Next Level

17. Data Visualization Cookbook

18. High-performance Computing

19. Text Mining

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