Statistical Techniques for Data Analysis, Second Edition

While intended for self-study, the book can also be used as a text for a short course introducing statistical analysis or as a supplement for undergraduate and graduate majors in physical sciences and engineering.

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

WHAT ARE DATA?Definition of Data Kinds of Data Variability Populations and SamplesImportance of Reliability MetrologyComputer Assisted Statistical Analyses Exercises ReferencesOBTAINING MEANINGFUL DATAData Production Must Be Planned The Experimental MethodData Quality Indicators Data Quality Objectives Systematic Measurement Quality Assurance Importance of Peer ReviewExercises ReferencesGENERAL PRINCIPLESIntroductionKinds of Statistics DecisionsError and UncertaintyKinds of Data Accuracy, Precision, and BiasStatistical ControlDistributionsTests for Normality Basic Requirements for Statistical Analysis ValidityMINITAB Exercises ReferencesSTATISTICAL CALCULATIONSIntroductionThe Mean, Variance, and Standard DeviationDegrees of FreedomUsing Duplicate Measurements to Estimate a Standard Deviation Using the Range to Estimate the Standard Deviation Pooled Statistical Estimates Simple Analysis of VarianceLog Normal StatisticsMinimum Reporting Statistics Computations One Last Thing to Remember Exercises ReferencesDATA ANALYSIS TECHNIQUESIntroductionOne Sample Topics Two Sample Topics Propagation of Error in a Derived or Calculated Value Exercises ReferencesMANAGING SETS OF DATAIntroduction Outliers Combining Data Sets Statistics of Interlaboratory Collaborative Testing Random Numbers Exercises References PRESENTING DATATables Charts Graphs Mathematical Expressions Exercises References PROPORTIONS, SURVIVAL DATA AND TIME SERIES DATAIntroduction Proportions Survival Data Time Series Data Exercises References SELECTED TOPICSBasic 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 CONCLUSIONSummary APPENDICESStatistical Tables GlossaryAnswers to Numerical Exercises Index

Taylor\, John K.; Cihon\, Cheryl