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Using R for Introductory Statistics
The Basic Library List Committee suggests that undergraduate mathematics libraries consider this book for acquisition.
See our review of the first edition. The major changes for the second edition have to do with R: the latest version is now used, students and instructors are encouraged to use RStudio and "more idiomatic" R. On the statistics side, a small amount of material dealing with Bayesian analysis, resampling methods, and permutation tests has been added.
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
Dummy View - NOT TO BE DELETED