Six Sigma Distribution Modeling Distribution models are essential tools for Estimating process characteristics Predicting future values Simulating process behavior Communicating random concepts

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Six Sigma Distribution Modeling is the first book providing expert guidance on selecting distribution models, plus a comprehensive catalog of distribution families. Written for non-statisticians, this landmark reference makes it easy to choose a properly fitting distribution model and use it for a variety of important tasks.

Six Sigma training and many statistical tools assume that processes have a normal distribution. When they do not, statistical tools must be changed to fit the process. Six Sigma Distribution Modeling illustrates the best ways to create control charts, calculate capability metrics, and predict process performance using a wide variety of distribution models.

No other book provides expert guidance on all these important tools:

• Goodness-of-fit tests

• Graphs for selecting distributions

•  Estimating population characteristics

•  Nonnormal capability metrics

•  Nonnormal control charts

•  Optimizing random processes

•  Extreme value theory

• Selecting and using statistical software

Table of Contents:

1. Modeling random behavior with probability distributions

2. Selecting statistical software tools for Six Sigma practitioners

3. Applying nonnormal distribution models in Six Sigma projects

4. Applying distribution models and simulation in Six Sigma projects

5. Glossary of Terms

6. Bernoulli (Yes-No) distribution

7. Beta distribution

8. Binomial distribution

9. Chi-squared distribution, including chi and noncentral versions

10. Discrete uniform distribution

11. Exponential distribution

12. Extreme value distribution

13. F distribution, including noncentral version

14. Gamma distribution

15. Geometric distribution

16. Hypergeometric distribution

17. Laplace distribution

18. Logistic distribution

19. Lognormal distribution

20. Negative binomial distribution

21. Normal (Gaussian) distribution, including half-normal and truncated versions

22. Pareto distribution

23. Poisson distribution, including truncated versions

24. Rayleigh distribution

25. Student’s t distribution, including noncentral version

26. Triangular distribution

27. Uniform distribution

28. Weibull distribution