Statistics Books
This is a list of some of my favorite statistics books. For each book, full bibliographic
information is given, along with a brief summary and/or review of the book. Each book
also offers a link to purchase the book directly from
Amazon.com.
If you see a book you like, you can click on the title to order it and have a copy delivered
to your door.
If you have any comments or questions about the books listed here, or if you'd like to give me
suggestions about other books you'd like to see on the list, please
send me a message.
If you don't see the book you're looking for here, you can do a search at Amazon.com. See the
search form at the end of this page.
The books are categorized as follows:
Massmarket statistics books

Against the Gods: the
Remarkable Story of Risk by Peter Bernstein

This wellcrafted book traces the history of probabilistic thought and its application to measuring
and controlling risk. If you are interested in statistics, you'll love this book; if you have only
a passing interest in statistics or probability, you'll still find this a basically enjoyable read.
Bernstein, P. (1996). Against the Gods: the Remarkable Story of Risk. New York: Wiley.

The Cartoon Guide to Statistics by Gonick and Smith

This book gives a gentle introduction to statistics in cartoon format. It's actually
surprisingly effectivethe visual approach makes statistical concepts easy to grasp.
Recommended for anyone who needs to get a feel for what statistics are all about and
the basic reasoning behind statistical methods, but doesn't want to wade through a traditional
textbook.
Gonick, L. and Smith, W. (1993). The Cartoon Guide to Statistics. New York: Harper Collins.

How to Lie with Statistics by Darrell Huff

A classic, written in 1954 but every bit as relevant today as it was then. This book describes
how, if misused, statistics can lead people far astray. Many pitfalls are described in humorous
fashion, along with suggestions for how to avoid problems.
Huff, D. (1993). How to Lie with Statistics. New York: W. W. Norton & Co.

Innumeracy: Mathematical
Illiteracy and Its Consequences by John Allen Paulos

An insightful look into the phenomenon of mathematical illiteracy, some of the causes of it, the
detrimental effects of it, and ways to improve the situation. One example: people
who refuse to travel due to fear of terrorism, when the risk of being killed in an auto accident is
roughly 300 times greater than the risk of dying at the hands of terrorists. By encouraging readers
to develop a feel for numbers (especially large ones) and an appreciation for the workings of
probability, he does much to combat innumeracy (at least in his readers).
Paulos, J. A. (1988). Innumeracy: Mathematical Illiteracy and Its
Consequences. New York: Vintage Books.
Back to top
Linear models (and extensions)

Generalized Linear Models by McCullagh and Nelder

This book gives a nice overview of how linear models can be generalized to derive things like
loglinear models and survival models (Cox's proportional hazards model). A bit dense in places, but
a worthwhile read, and a nice reference to have handy.
McCullagh, P. and Nelder, J. A. (1989). Generalized Linear Models. New York: Chapman & Hall.

Applied Linear Statistical Models
by Neter, Kutner, Nachtsheim, and Wasserman

This book gives comprehensive coverage of linear models, including simple regression, multiple
regression, analysis of variance (ANOVA), and some coverage of experimental designs. Very thorough,
an invaluable reference book.
Neter, J., Kutner, M. H., Nachtsheim, C. J., & Wasserman, W. (1996). Applied Linear Statistical
Models. Chicago: Irwin.

Statistical Methods:
the Geometric Approach by Saville and Wood

This book covers linear models (ANOVA and Regression) from a geometric point of view, in terms of
projections of the data on model and error spaces. A very unusual approach, but quite effective,
especially for those who think in visual terms more than mathematical terms.
Saville, D. J. and Wood, G. R. (1991). Statistical Methods: the Geometric Approach. New York:
SpringerVerlag.
Back to top
Design of Experiments
A note to social science researchers: most of the books listed here discuss experimental
design from an engineering perspective, which is somewhat different from the social science approach.
In industrial settings, experimental designs generally focus on efficiency, emphasizing fractional
factorial designs and polynomial response surface models, and usually with little or no coverage
of the repeated measures (AKA withinsubjects) designs so familiar to social scientists. In contrast,
most books aimed at social scientists tend not to do much with fractional designs (coverage is
usually restricted to discussion of Latin square designs), but give indepth information on
repeated measures designs. Books with this emphasis will be clearly identified in the list.

Statistics for Experimenters by Box, Hunter, and Hunter

This is a classic in design of experiments. A lot of indepth information about
design of experiments, including fractional factorial designs. Also includes some
coverage of response surface designs. The emphasis is on getting usable results, combining the
traditional statistical tools (e.g. ANOVA) with plotting of results to show important effects at
a glance. Highly recommended!
Box, G. E. P., Hunter, W. G. and Hunter, J. S. (1978). Statistics for Experimenters.
New York: Wiley.

Experiments with Mixtures
by John Cornell

Experiments involving mixtures, where the sum of the mixture components must equal some constant
(usually 1.0), require specialized methods. This book is the definitive reference for such
experiments, covering a variety of design approaches, analysis problems, and practical advice.
Cornell, J.A. (1990). Experiments with Mixtures. New York: Wiley.

Statistical Design and Analysis of Experiments by Peter W. M. John

This old text has recently been reprinted by SIAM in their Classics in Applied Mathematics
series. I found this to be a very good book, with plenty of examples to illustrate the concepts. The
book was originally published in 1971 and has not been updated, so some more recent developments in
experimental design are not covered.
John, P. W. M. (1998). Statistical Design and Analysis of Experiments. Philadelphia: SIAM.

Design and Analysis : A Researcher's Handbook by Geoffrey Keppel

This is a socialscience oriented treatment of experimental design, aimed at a first or second
graduatelevel course in statistics. Emphasis is on ANOVA, including fullfactorial designs, and
a whole section (four chapters) on withinsubjects (repeated measures) designs. No coverage of
response surface designs (though some discussion of "trend analysis" can be found), and coverage
of fractional designs is limited to Latin square designs. A nice reference for the beginning social
science researcher.
Keppel, G. (1991). Design and Analysis : A Researcher's Handbook. Englewood Cliffs, NJ: PrenticeHall.
Back to top
Multivariate statistics

Multivariate Analysis:
Methods and Applications by Dillon and Goldstein

This book gives good coverage of several multivariate techniques, including cluster analysis and
multidimensional scaling in addition to the more common techniques like factor analysis,
multiple regression, and discriminant analysis. Everything is explained in clear language, so
you don't have to be a mathematician to follow the text.
Dillon, W. R. and Goldstein, M. (1984). Multivariate Analysis: Methods and Applications.
New York: Wiley.

Using Multivariate Statistics by Tabachnick and Fidell

A very nice book that covers a wide variety of multivariate statistical applications. Focuses on
practical aspects of multivariate data analysis, and is very accessible. Also included are examples
of output from various statistical software packages. This book is a nice
reference to have handy. My only complaint: no coverage of cluster analysis.
Tabachnick, B. G., and Fidell, L. S. (1996). Using Multivariate Statistics. New York:
HarperCollins College Publishers.
Back to top
Categorical data analysis

Categorical Data Analysis by Alan Agresti

This book is a musthave for anyone doing serious data analysis with categorical variables.
Covers techniques from simple chisquare methods through loglinear models, models for ordinal data,
models for matched pairs, repeated categorical response data, and parametric models for
categorical data.
Agresti, A. (1990). Categorical Data Analysis. New York: Wiley.
Back to top
Structural equation modeling

Structural Equations with Latent Variables by Kenneth Bollen

The reference book for structural equation modeling. Goes into more depth on the subject
than any other book I've seen. Covers everything from the basics up to diagnosing problematic
models and the subtleties of different estimation methods and fit indices. The book was written over
10 years ago, so some of
the material is a bit out of date, but the foundations are still solid, and this book should still
be required reading for serious structural equation modelers.
Bollen, K. (1987). Structural Equations with Latent Variables. New York: Wiley.

Structural Equation
Modeling: Concepts, Issues, and Applications edited by Rick Hoyle

This is a nice collection of chapters by some of the top researchers in SEM. Gives a good grounding
in the basics, as well as introducing some of the controversies surrounding SEMs (e.g. when to use
which fit index). Also includes chapters of a more practical nature, such as writing about SEM models
and a comparison of two software packages, and some examples of reallife SEM research.
Hoyle, R. H. (1995). Structural Equation Modeling: Concepts, Issues, and Applications.
Thousand Oaks, CA: Sage.
Back to top
Visualization and graphics

The Visual Display of Quantitative Information,
Envisioning Information,
Visual Explanations: Images and Quantities, Evidence and Narrative
all by Edward Tufte

These books by a master of data visualization are must reading for anyone who
generates charts and graphs. Tufte doesn't just dwell on specifics of graphing techniqueshe
presents a philosophy of data visualization, one that harnesses creativity as well as rigor
to effectively and accurately convey information (as opposed to many examples seen in the popular
media, where
"creativity" often obscures and distorts the informational message). Even the books themselves
are things of beautythe layout is very elegant, making the books a pleasure to read.
Tufte, E. R. (1983). The Visual Display of Quantitative Information. Cheshire, CT:
Graphics Press.
Tufte, E. R. (1990). Envisioning Information. Cheshire, CT: Graphics Press.
Tufte, E. R. (1997). Visual Explanations: Images and Quantities, Evidence and Narrative.
Cheshire, CT: Graphics Press.
Back to top
Exploratory data analysis, data mining, and KDD

Data Mining Techniques for Marketing, Sales, and Customer Support by Berry and
Linoff

This is a nice introduction to data mining in the context of real business problems. The book
is written at a very accessible level, and includes many examples of real datamining situations
to illustrate the points in the book.
Berry, M. J. A. and Linoff, G. (1997). Data Mining Techniques for Marketing, Sales, and Customer
Support. New York: Wiley.

Data Warehousing, Data Mining, and OLAP by Berson and Smith

This comprehensive (and large!) book covers a wide range of topics, with souptonuts coverage of assembling and maintaining a
data warehouse and using various techniques (statistical and other) to get useful information out of it. Puts data mining
in the larger context of decision support. Lots of good practical information, including sections on "ten
mistakes for data warehousing managers to avoid" and "big databetter returns: leveraging your hidden
data assets to improve ROI."
Berson, A. and Smith, S. J. (1997). Data Warehousing, Data Mining, and OLAP. New York:
McGrawHill.

Exploratory Data Analysis by John Tukey

Decades before "data mining" came into vogue, Tukey wrote this classic book that defined an entire
subdiscipline of statistics. Some of the material is based on outdated technologywritten in 1977,
it assumes the reader doesn't have access to computers with graphical capabilities. However, the
fundamental ideas are even more relevant today than they were when the book was written. With
highspeed PC's at everyone's beck and call and tons of archived data available, everyone is trying
to sift through their data to find something "interesting"it's more important than ever to make
sure that exploratory data analysis is done well.
Tukey, J. W. (1977). Exploratory Data Analysis. Reading, MA: AddisonWesley.
Back to top
Statistical reference books

Finding Statistics Online by Paula Berinstein

This is a nice reference that helps you find statistics in electronic resources,
including (but not limited to) the Internet. A nice book to have around if you
often need to dig up specific statistics. Note that this will not help you find
information on statistical methodsit will help you find specific numbers,
e.g. the population of Lithuania or the number of Roman Catholics in the U.S.
One caveat: avoid the chapter on "Statistics Basics". There are some errors in
this chapter that may mislead novices (and irk statisticians). If
you skip this chapter, the rest of the book is very useful.
Berinstein, P. (1998). Finding Statistics Online: How to Locate the
Elusive Numbers You Need. Medford, NJ: Information Today.

Cambridge Dictionary of Statistics by B. S. Everitt

This is a valuable reference to have on the shelf. Gives concise but thorough definitions of
most of the important terminology used in statistics. An essential tool for people who write about
(or read about) statistics.
Everitt, B. S. (1998). The Cambridge Dictionary of Statistics. New York: Cambridge University
Press.

Encyclopedia of Statistical Sciences edited by Samuel Kotz

This 9 volume set (plus updates) is a tremendous asset to any statistics library. Gives brief but
complete background information on most topics in statistical theory and practice. This reference is
too pricey for most individuals (almost $2000 for the 9volume set), but it's definitely a
worthwhile investment for institutional librariesor for those independently wealthy statisticians
among us.
Kotz, S. (1988). Encyclopedia of Statistical Sciences, vol. 19 plus supplements. New York:
Wiley.
Back to top
Search for books
This page maintained by Clay Helberg. Last updated
March 8, 1999