Using R for statistics

by Stowell, Sarah

Type Book

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Title Statements

Full title :Using R for statistics / Sarah Stowell.

Summary

R is a popular and growing open source statistical analysis and graphics environment as well as a programming language and platform. You'll be able to navigate the R system, enter and import data, manipulate datasets, calculate summary statistics, create statistical plots and customize their appearance, perform hypothesis tests such as the t-tests and analyses of variance, and build regression models. Examples are built around actual datasets to simulate real-world solutions, and programming basics are explained to assist those who do not have a development background. No prior knowledge of R or of programming is assumed, though you should have some experience with statistics. What you'll learn: How to apply statistical concepts using R and some R programming; How to work with data files, prepare and manipulate data, and combine and restructure datasets; How to summarize continuous and categorical variables; What is a probability distribution; How to create and customize plots; How to do hypothesis testing; How to build and use regression and linear models. --

Edition Statements

Publication Date:©2014

Publication Statements

Publisher(s):Apress
Place of Publication:Berkeley, CA
Language:eng
Publication Date:©2014

The Physical Object

Description:1 online resource (xvi, 250 pages) : : illustrations

Edition Identifiers

ISBN:9781484201398, 1484201396
DOI:10.1007/978-1-4842-0139-8
oclc:ocn883395168
LC Classification:QA276.4
Dewey Decimal:519.50285/5133

At a Glance; Introduction; Chapter 1: R Fundamentals; Downloading and Installing R; Getting Orientated; The R Console and Command Prompt; Functions; Objects; Simple Objects; Vectors; Data Frames; The Data Editor; Workspaces; Error Messages; Script Files; Summary; Chapter 2: Working with Data Files; Entering Data Directly; Importing Plain Text Files; CSV and Tab-Delimited Files; DIF Files; Other Plain Text Files; Importing Excel Files; Importing Files from Other Software; Using Relative File Paths; Exporting Datasets; Summary; Chapter 3: Preparing and Manipulating Your Data; Variables.

Rearranging and Removing VariablesRenaming Variables; Variable Classes; Calculating New Numeric Variables; Dividing a Continuous Variable into Categories; Working with Factor Variables; Manipulating Character Variables; Concatenating Character Strings; Extracting a Substring; Searching a Character Variable; Working with Dates and Times; Adding and Removing Observations; Adding New Observations; Removing Specific Observations; Removing Duplicate Observations; Selecting a Subset of the Data; Selecting a Subset According to Selection Criteria; Selecting a Random Sample from a Dataset.

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