Statistical Techniques for Data Analysis, Second Edition

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ISBN 9781584883852
Cat# C3855
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ISBN 9780203492390
Cat# TFE945
 

Features

  • "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

    Table of Contents

    WHAT ARE DATA?
    Definition of Data
    Kinds of Data
    Variability
    Populations and Samples
    Importance of Reliability
    Metrology
    Computer Assisted Statistical Analyses
    Exercises
    References
    OBTAINING MEANINGFUL DATA
    Data Production Must Be Planned
    The Experimental Method
    Data Quality Indicators
    Data Quality Objectives
    Systematic Measurement
    Quality Assurance
    Importance of Peer Review
    Exercises
    References
    GENERAL PRINCIPLES
    Introduction
    Kinds of Statistics
    Decisions
    Error and Uncertainty
    Kinds of Data
    Accuracy, Precision, and Bias
    Statistical Control
    Distributions
    Tests for Normality
    Basic Requirements for Statistical Analysis Validity
    MINITAB
    Exercises
    References
    STATISTICAL CALCULATIONS
    Introduction
    The Mean, Variance, and Standard Deviation
    Degrees of Freedom
    Using Duplicate Measurements to Estimate a Standard Deviation
    Using the Range to Estimate the Standard Deviation
    Pooled Statistical Estimates
    Simple Analysis of Variance
    Log Normal Statistics
    Minimum Reporting Statistics
    Computations
    One Last Thing to Remember
    Exercises
    References
    DATA ANALYSIS TECHNIQUES
    Introduction
    One Sample Topics
    Two Sample Topics
    Propagation of Error in a Derived or Calculated Value
    Exercises
    References
    MANAGING SETS OF DATA
    Introduction
    Outliers
    Combining Data Sets
    Statistics of Interlaboratory Collaborative Testing
    Random Numbers
    Exercises
    References
    PRESENTING DATA
    Tables
    Charts
    Graphs
    Mathematical Expressions
    Exercises
    References
    PROPORTIONS, SURVIVAL DATA AND TIME SERIES DATA
    Introduction
    Proportions
    Survival Data
    Time Series Data
    Exercises
    References
    SELECTED TOPICS
    Basic Probability Concepts
    Measures of Location
    Tests for Nonrandomness
    Comparing Several Averages
    Type I Errors, Type II Errors and Statistical Power
    Critical Values and P Values
    Correlation Coefficient
    The Best Two Out of Three
    Comparing a Frequency Distribution with a Normal Distribution
    Confidence for a Fitted Line
    Joint Confidence Region for the Constants of a Fitted Line
    Shortcut Procedures
    Nonparametric Tests
    Extreme Value Data
    Statistics of Control Charts
    Simulation and Macros
    Exercises
    References
    CONCLUSION
    Summary
    APPENDICES
    Statistical Tables
    Glossary
    Answers to Numerical Exercises
    Index