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Using R for Introductory Statistics (Verzani)


 
 
 Author(s)  John Verzani
 Title  Using R for Introductory Statistics
 Edition  1st
 Year  2004
 Publisher  Chapman Hall/CRC Press
 ISBN  978-1584884507
 Website  Publisher website:
 http://www.crcpress.com/product/isbn/9781584884507

 simpleR website: (early notes for the book)
 http://www.math.csi.cuny.edu/Statistics/R/simpleR/Simple

 The printable .pdf version of the simpleR notes may be found at:
 http://cran.r-project.org/doc/contrib/Verzani-SimpleR.pdf
 

This book has an accompanying set of computer files. If there is internet availability, these may be installed within an R session using the menu bar (if present) or the command

> install.packages("UsingR")


Table of Contents

Introduction

What is R

A note on notation

Data

Starting

Entering data with

Data is a vector 

Problems

 

Univariate Data

Categorical data

Numerical data

Problems

 

Bivariate Data

Handling bivariate categorical data

Handling bivariate data: categorical vs. numerical

Bivariate data: numerical vs. numerical

Linear regression

Problems

 

Multivariate Data

Storing multivariate data in data frames

Accessing data in data frames

Manipulating data frames: stack and unstack

Using R's model formula notation

Ways to view multivariate data

The lattice package

Problems

 

Random Data

Random number generators in R{ the \r" functions

Problems

 

Simulations

The central limit theorem

Using simple.sim and functions

Problems

 

Exploratory Data Analysis

Our toolbox

Examples

Problems

 

Confidence Interval Estimation

Population proportion theory

Proportion test

The z-test

The t-test

Confidence interval for the median

Problems

 

Hypothesis Testing

Testing a population parameter

Testing a mean

Tests for the median

Problems

 

Two-sample tests

Two-sample tests of proportion

Two-sample t-tests

Resistant two-sample tests

Problems

 

Chi Square Tests

The chi-squared distribution

Chi-squared goodness of  t-tests

Chi-squared tests of independence

Chi-squared tests for homogeneity

Problems

 

Regression Analysis

Simple linear regression model

Testing the assumptions of the model

Statistical inference

Problems

 

Multiple Linear Regression

The model

Problems

 

Analysis of Variance

one-way analysis of variance

Problems

 

Appendix: Installing R

Appendix: External Packages

Appendix: A sample R session

A sample session involving regression

t-tests

A simulation example

 Appendix: What happens when R starts?

Appendix: Using Functions

The basic template

For loops

Conditional expressions

Appendix: Entering Data into

Using c

using scan

Using scan with a _le

Editing your data

Reading in tables of data

Fixed-width _elds

Spreadsheet data

XML, urls

\Foreign" formats

 Appendix: Teaching Tricks

 Appendix: Sources of help, documentation





 
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