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Using R for Introductory Statistics

Publisher: 
Chapman & Hall/CRC
Number of Pages: 
414
Price: 
53.95
ISBN: 
9781584884507

The author has made a very serious effort to introduce entry-level students of statistics to the open-source software package R. One mistake most authors of similar texts make is to assume some basic level of familiarity, either with the subject to be taught, or the tool (the software package) to be used in teaching the subject.

This book does not fall into either trap. About one-fifth of the book is a collection of Appendices that explains how to install the software package in your computer for three different operating systems, how to use interfaces, graphics, and how to program. This is great, since this will broaden the reach of the book by attracting self-instructing readers who otherwise would not know how to start.

As far as the text itself goes, the examples and exercises are well-chosen; they concern questions to which we would actually like to know the answer. Topical coverage is comparable to more traditional introductory textbooks, though the treatment is somewhat less formal than the average.

My only critical remark is that none of the exercises and problems have their solution included in the book. I do understand that there is a website with selected solutions, and that instructors can receive a full solution manual. I also understand that the book involves the use of R, and therefore, the student using the book will spend a lot of time at a computer, so that it's not unreasonable to assume that he or she might as well check the solutions on the web. Still, we do not want to send the message that without immediate access to a software package, our fresh knowledge is useless, and indeed, there are a few exercises in the book that can be solved just by thinking. A few of these should have their solutions in the book, to encourage that kind of learning as well.


Miklós Bóna is Professor of Mathematics at the University of Florida.


Date Received: 
Tuesday, October 5, 2010
Reviewable: 
Yes
Include In BLL Rating: 
Yes
John Verzani
Publication Date: 
2005
Format: 
Hardcover
Audience: 
Category: 
Textbook
Miklós Bóna
10/28/2010
BLL Rating: 

DATA
What Is Data?
Some R Essentials
Accessing Data by Using Indices
Reading in Other Sources of Data
UNIVARIATE DATA
Categorical Data
Numeric Data
Shape of a Distribution
BIVARIATE DATA
Pairs of Categorical Variables
Comparing Independent Samples
Relationships in Numeric Data
Simple Linear Regression
MULTIVARIATE DATA
Viewing Multivariate Data
R Basics: Data Frames and Lists
Using Model Formula with Multivariate Data
Lattice Graphics
Types of Data in R
DESCRIBING POPULATIONS
Populations
Families of Distributions
The Central Limit Theorem
SIMULATION
The Normal Approximation for the Binomial
for loops
Simulations Related to the Central Limit Theorem
Defining a Function
Investigating Distributions
Bootstrap Samples
Alternates to for loops
CONFIDENCE INTERVALS
Confidence Interval Ideas
Confidence Intervals for a Population Proportion, p
Confidence Intervals for the Population Mean, µ
Other Confidence Intervals
Confidence Intervals for Differences
Confidence Intervals for the Median
SIGNIFICANCE TESTS
Significance Test for a Population Proportion
Significance Test for the Mean (t-Tests)
Significance Tests and Confidence Intervals
Significance Tests for the Median
Two-Sample Tests of Proportion
Two-Sample Tests of Center
GOODNESS OF FIT
The Chi-Squared Goodness-of-Fit Test
The Chi-Squared Test of Independence
Goodness-of-Fit Tests for Continuous Distributions
LINEAR REGRESSION
The Simple Linear Regression Model
Statistical Inference for Simple Linear Regression
Multiple Linear Regression
ANALYSIS OF VARIANCE
One-Way ANOVA
Using lm() for ANOVA
ANCOVA
Two-Way ANOVA
TWO EXTENSIONS OF THE LINEAR MODEL
Logistic Regression
Nonlinear Models
APPENDIX A: GETTING, INSTALLING, AND RUNNING R
Installing and Starting R
Extending R Using Additional Packages
APPENDIX B: GRAPHICAL USER INTERFACES AND R
The Windows GUI
The Mac OS X GUI
Rcdmr
APPENDIX C: TEACHING WITH R
APPENDIX D: MORE ON GRAPHICS WITH R
Low- and High-Level Graphic Functions
Creating New Graphics in R
APPENDIX E: PROGRAMMING IN R
Editing Functions
Using Functions
Using Files and a Better Editor
Object-Oriented Programming with R
INDEX

Publish Book: 
Modify Date: 
Tuesday, January 18, 2011

Dummy View - NOT TO BE DELETED