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This volume introduces the relationship of statistics, probability, and reliability as they apply to quality in general and to Six Sigma in particular. The author brings the theoretical into the practical by providing statistical techniques, tests, and methods that the reader can use in any organization. He reviews basic parametric and non-parametric statistics, probability concepts and applications, and addresses topics for both measurable and attribute characteristics. He delineates the importance of collecting, analyzing, and interpreting data not from an academic point of view but from a practical perspective.
Inhaltsverzeichnis
STATISTICAL CONCEPTS. Designing a Study. Counting Responses for Single Variable. Summarizing Data. Counting Responses for Combinations. Changing the Coding Scheme. Looking at Means. Means from Samples. Working with the Normal Distribution. Testing Hypothesis - Two Independent Means. Testing Hypothesis - Two Dependent Means. Testing Hypothesis about Independence. Comparing Several Means. Plotting Data. Regression. PROBABILITY CHANGES. Set Theory and Venn Diagrams. Probability Concepts. Discrete and Random Variables. Binomial and Poison Distributions. Continuous and Uniform Distributions. Normalizing Binomial and Central Limit Theorem. Functions of Random Variables. Exponential Distribution and Reliability. Poison Process. Chi Square Distribution. T Distribution. Sample Size for Mean Distribution. Sampling Theory. Probability Plots and Percentiles. RELIABILITY CONCEPTS. Failure Rates. Reliability Rate. MTBF. MTBR. ROCOF Plot. Weibull Distribution. Gamma Distribution and Reliability. Hypothesis Testing and OC Curves. Least Squares and Regression Analysis. Taylor Series Expansion.
Über den Autor / die Autorin
D.H. Stamatis
Zusammenfassung
Explaining probability issues as they relate to Six Sigma, this book introduces the relationship of statistics, probability, and reliability as they apply to quality in general and to Six Sigma in particular. This book reviews basic parametric and non-parametric statistics, probability concepts, and applications.
