Title:
Six sigma distribution modeling
Personal Author:
Publication Information:
New York, NY : McGraw-Hill, 2007
ISBN:
9780071482783
Available:*
Library | Item Barcode | Call Number | Material Type | Item Category 1 | Status |
---|---|---|---|---|---|
Searching... | 30000010129236 | TS156 S534 2007 | Open Access Book | Book | Searching... |
On Order
Summary
Summary
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.
Author Notes
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 FDistribution 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 |