Statistical Techniques for Data Analysis, Second Edition

ISBN-13: 9781584883852 / Angielski / Twarda / 2004 / 294 str.

Cheryl Cihon; John K. Taylor; Taylor K. Taylor

Opis

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

Spis treści

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

O autorze

Taylor\, John K.; Cihon\, Cheryl