Statistical Techniques for Data Analysis

Statistical Techniques for Data Analysis

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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 analysisshow more

Product details

  • Hardback | 296 pages
  • 153.4 x 240.8 x 21.6mm | 553.39g
  • Taylor & Francis Inc
  • Chapman & Hall/CRC
  • Boca Raton, FL, United States
  • English
  • Revised
  • 2nd Revised edition
  • 42 black & white illustrations, 45 black & white tables, 2 black & white halftones
  • 1584883855
  • 9781584883852
  • 2,387,056

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 Indexshow more

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