Six Sigma Distribution Modeling
Author: Andrew D Sleeper
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.
Andrew Sleeper is a Master Black Belt and General Manager of Successful Statistics, LLC. Since 1981, he has worked with product development teams as an engineer, statistician, project manager, Six Sigma Black Belt, and consultant. An experienced instructor of statistical tools for engineers, Mr. Sleeper has presented thousands of hours of training in countries around the world. Mr. Sleeper is also the author of Design For Six Sigma Statistics: 59 Tools for Diagnosing and Solving Problems in DFSS Initiatives, published by McGraw-Hill.
Table of Contents:
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
New interesting textbook: Easy Everyday or Cranberry Companion
How to Do Everything with Microsoft Office Infopath 2003 (How to Do Everything Series)
Author: David McAmis
Tap into the power of the newest member of Microsoft’s Office suite. Learn to use InfoPath’s robust set of tools to capture information that’s locked away in document-based forms. Quickly create forms and data-gathering applications that use XML to separate form and content. This “raw” information can then be integrated into back-end systems, providing an end-to-end solution for data capture in the enterprise.
No comments:
Post a Comment