Overview

Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product. Sleeper provides six sigma practitioners with the tools which will allow them to stand out from your competitors by using advanced statistical and modeling tools for more in-depth analysis. Understanding and properly utilizing statistical data distributions is one of the most important and difficult skills for a six sigma practitioner to possess. Sleeper provides six sigma practitioners with a road map for selecting and using distributions for more precise outcomes. With the added value of Crystal Ball Modeling software, this book becomes a powerful tool for analyzing and modeling difficult data quickly and efficiently.

Full Product Details

Author:   Andrew Sleeper
Publisher:   McGraw-Hill Education - Europe
Imprint:   McGraw-Hill Professional
Dimensions:   Width: 15.80cm , Height: 2.90cm , Length: 22.90cm
Weight:   0.775kg
ISBN:  

9780071482783

ISBN 10:   0071482784
Pages:   448
Publication Date:   16 January 2007
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Unknown
Availability:   In Print  
Limited stock is available. It will be ordered for you and shipped pending supplier's limited stock.

Table of Contents

Chapter 1: Modeling Random Behavior with Probability DistributionsChapter 2: Selecting Statistical Software Tools for Six Sigma PractitionersChapter 3: Applying Nonnormal Distribution Models in Six Sigma ProjectsChapter 4: Applying Distribution Models and Simulation in Six Sigma ProjectsChapter 5: Glossary of TermsChapter 6: Bernouli (Yes-No) Distribution FamilyChapter 7: Beta Distribution FamilyChapter 8: Binomial Distribution FamilyChapter 9: Chi-Squared Distribution FamilyChapter 10: Discrete Uniform Distribution FamilyChapter 11: Exponential Distribution FamilyChapter 12: Extreme Value (Gumbel) Distribution FamilyChapter 13: F Distribution FamilyChapter 14: Gamma Distribution FamilyChapter 15: Geometric Distribution FamilyChapter 16: Hypergeometric Distribution FamilyChapter 17: Laplace Distribution FamilyChapter 18: Logistic Distribution FamilyChapter 19: Logonormal Distribution FamilyChapter 20: Negative Binomial Distribution FamilyChapter 21: Normal (Gaussian) Distribution FamilyChapter 22: Pareto Distribution FamilyChapter 23: Poisson Distribution FamilyChapter 24: Rayleigh Distribution FamilyChapter 25: Student's Distribution FamilyChapter 26: Triangular Distribution FamilyChapter 27: Uniform Distribution FamilyChapter 28: Weibull Distribution FamilyREFERENCESINDEX

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