ISBN10: 0071482784 | ISBN13: 9780071482783

Six Sigma Distribution Modeling, 1st Edition

ISBN10: 0071482784

ISBN13: 9780071482783

By Andrew Sleeper

ISBN10: 0071712496 | ISBN13: 9780071712491

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ISBN10: 0071482784 | ISBN13: 9780071482783

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ISBN10: 0071712496 | ISBN13: 9780071712491

More information about this eBook can be found in the page section below.

ISBN10: 0071482784 | ISBN13: 9780071482783

More information about this Print book can be found in the page section below.

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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.

Chapter 1: Modeling Random Behavior with Probability Distributions

Chapter 2: Selecting Statistical Software Tools for Six Sigma Practitioners

Chapter 3: Applying Nonnormal Distribution Models in Six Sigma Projects

Chapter 4: Applying Distribution Models and Simulation in Six Sigma Projects

Chapter 5: Glossary of Terms

Chapter 6: Bernouli (Yes-No) Distribution Family

Chapter 7: Beta Distribution Family

Chapter 8: Binomial Distribution Family

Chapter 9: Chi-Squared Distribution Family

Chapter 10: Discrete Uniform Distribution Family

Chapter 11: Exponential Distribution Family

Chapter 12: Extreme Value (Gumbel) Distribution Family

Chapter 13: F Distribution Family

Chapter 14: Gamma Distribution Family

Chapter 15: Geometric Distribution Family

Chapter 16: Hypergeometric Distribution Family

Chapter 17: Laplace Distribution Family

Chapter 18: Logistic Distribution Family

Chapter 19: Logonormal Distribution Family

Chapter 20: Negative Binomial Distribution Family

Chapter 21: Normal (Gaussian) Distribution Family

Chapter 22: Pareto Distribution Family

Chapter 23: Poisson Distribution Family

Chapter 24: Rayleigh Distribution Family

Chapter 25: Student's Distribution Family

Chapter 26: Triangular Distribution Family

Chapter 27: Uniform Distribution Family

Chapter 28: Weibull Distribution Family

REFERENCES

INDEX

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