Statistical Techniques for Data Analysis

2nd Edition

John K. Taylor, Cheryl Cihon

Chapman and Hall/CRC
Published January 14, 2004
Reference - 296 Pages - 42 B/W Illustrations
ISBN 9781584883852 - CAT# C3855

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  • "Presents the material from a practical, nonmathematical perspective in an informal, very readable style-requires no prior knowledge of statistics
  • "Provides step-by-step MINITAB procedures and data sets in the examples so readers can duplicate the calculations and obtain the desired output
  • "Explains each area of application and each technique in a correct scientific context
  • "Includes exercises in each chapter
  • Summary

    Since the first edition of this book appeared, computers have come to the aid of modern experimenters and data analysts, bringing with them data analysis techniques that were once beyond the calculational reach of even professional statisticians. Today, scientists in every field have access to the techniques and technology they need to analyze statistical data. All they need is practical guidance on how to use them.

    Valuable to everyone who produces, uses, or evaluates scientific data, Statistical Techniques for Data Analysis, Second Edition provides straightforward discussion of basic statistical techniques and computer analysis. The purpose, structure, and general principles of the book remain the same as the first edition, but the treatment now includes updates in every chapter, additional topics, and most importantly, an introduction to use of the MINITAB Statistical Software. The presentation of each technique includes motivation and discussion of the statistical analysis, a hand-calculated example, the same example calculated using MINITAB, and discussion of the MINITAB output and conclusions.

    Highlights of the Second Edition:

    " Detailed discussion and use of MINITAB in examples complete with code and output
    " A new chapter addressing proportions, time to event data, and time series data in the metrology setting
    " Additional material on hypothesis testing
    " Discussion of critical values
    " A look at mistakes commonly made in data analysis


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