Common Errors in Statistics: (and How to Avoid Them) / Edition 1

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Overview

A guide to choosing and using the right techniques

High-speed computers and prepackaged statistical routines would seem to take much of the guesswork out of statistical analysis and lend its applications readily accessible to all. Yet, as Phillip Good and James Hardin persuasively argue, statistical software no more makes one a statistician than a scalpel makes one a surgeon. Choosing the proper technique and understanding the analytical context is of paramount importance to the proper application of statistics. The highly readable Common Errors in Statistics (and How to Avoid Them) provides both newly minted academics and professionals who use statistics in their work with a handy field guide to statistical problems and solutions.

Good and Hardin begin their handbook by establishing a mathematically rigorous but readily accessible foundation for statistical procedures. They focus on debunking popular myths, analyzing common mistakes, and instructing readers on how to choose the appropriate statistical technique to address their specific task. A handy checklist is provided to summarize the necessary steps.

Topics covered include:

  • 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 others

Common Errors in Statistics (and How to Avoid Them) also contains reprints of classic articles from statistical literature to re-examine such bedrock subjects as linear regression, the analysis of variance, maximum likelihood, meta-analysis, and the bootstrap. With a final emphasis on finding solutions and on the great value of statistics when applied in the proper context, this book will prove eminently useful to students and professionals in the fields of research, industry, medicine, and government.

About the Author:
PHILLIP I. GOOD, PhD, is an Operations Manager for Information Research in Huntington Beach, California. He is the author of A Manager's Guide to the Design and Conduct of Clinical Trials, published by Wiley, as well as numerous other books.
JAMES W. HARDIN, PhD, is a lecturer and Assistant Research Scientist in the Department of Statistics at Texas A&M University.

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Product Details

  • ISBN-13: 9780471460688
  • Publisher: Wiley, John & Sons, Incorporated
  • Publication date: 7/11/2003
  • Edition description: Older Edition
  • Edition number: 1
  • Pages: 240
  • Product dimensions: 6.40 (w) x 9.22 (h) x 0.70 (d)

Table of Contents

Preface
Pt. I Foundations 1
1 Sources of Error 3
2 Hypothesis: The Why of Your Research 11
3 Collecting Data 25
Pt. II Hypothesis Testing and Estimation 39
4 Estimation 41
5 Testing Hypotheses: Choosing a Test Statistic 51
6 Strengths and Limitations of Some Miscellaneous Statistical Procedures 77
7 Reporting Your Results 91
8 Graphics 107
Pt. III Building a Model 127
9 Univariate Regression 129
10 Multivariate Regression 145
11 Validation 155
App. A 163
App. B 173
Glossary, Grouped by Related but Distinct Terms 187
Bibliography 191
Author Index 211
Subject Index 217
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  • Anonymous

    Posted July 8, 2003

    This book is available today (28 June 2003)

    Unbelievably Great! Ranks with such other outstanding texts as Permutation Tests, Resampling Methods, Applying Statistics in the Courtroom, and Manager's Guide to the Design of Clinical Trials.

    Was this review helpful? Yes  No   Report this review
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