Common Errors in Statistics (and How to Avoid Them) (PDF)

Praise for the First Edition of Common Errors in Statistics

" . . . let me recommend Common Errors to all those who interact
with statistics, whatever their level of statistical understanding
. . . "

--Stats 40

" . . . written . . . for the people who define good practice
rather than seek to emulate it."

--Journal of Biopharmaceutical Statistics

" . . . highly informative, enjoyable to read, and of potential use
to a broad audience. It is a book that should be on the reference
shelf of many statisticians and researchers."

--The American Statistician

" . . . I found this book the most easily readable statistics book
ever. The credit for this certainly goes to Phillip Good."

--E-STREAMS

A tried-and-true guide to the proper application of
statistics

Now in a second edition, the highly readable Common Errors in
Statistics (and How to Avoid Them) lays a mathematically rigorous
and readily accessible foundation for understanding statistical
procedures, problems, and solutions. This handy field guide
analyzes common mistakes, debunks popular myths, and helps readers
to choose the best and most effective statistical technique for
each of their tasks.

Written for both the newly minted academic and the professional who
uses statistics in their work, the book covers creating a research
plan, formulating a hypothesis, specifying sample size, checking
assumptions, interpreting p-values and confidence intervals,
building a model, data mining, Bayes' Theorem, the bootstrap, and
many other topics. The Second Edition has been extensively revised
to include:

* Additional charts and graphs

* Two new chapters, Interpreting Reports and Which Regression
Method?

* New sections on practical versus statistical significance and
nonuniqueness in multivariate regression

* Added material from the authors' online courses at
statistics.com

* New material on unbalanced designs, report interpretation, and
alternative modeling methods

With a final emphasis on both finding solutions and the great value
of statistics when applied in the proper context, this book is
eminently useful to students and professionals in the fields of
research, industry, medicine, and government.