Six Sigma and Beyond: Statistics and Probability, Volume III, 1st Edition (Hardback) book cover

Six Sigma and Beyond

Statistics and Probability, Volume III, 1st Edition

By D.H. Stamatis

CRC Press

368 pages | 139 B/W Illus.

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Hardback: 9781574443127
pub: 2002-08-28
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Researchers and professionals in all walks of life need to use the many tools offered by the statistical world, but often do not have the necessary experience in both concept and application. No matter what your profession, sooner or later numbers need to be crunched, and often you need to understand how to do it, and why it is important. Quality control is no different. Six Sigma and Beyond: Statistics and Probability covers the concepts of some useful statistical tools, appropriate formulae for specific tools, the connection of statistics to probability, and how to use them.

This volume introduces the relationship of statistics, probability, and reliability as they apply to quality in general and to Six Sigma in particular. The author brings the theoretical into the practical by providing statistical techniques, tests, and methods that the reader can use in any organization. He reviews basic parametric and non-parametric statistics, probability concepts and applications, and addresses topics for both measurable and attribute characteristics. He delineates the importance of collecting, analyzing, and interpreting data not from an academic point of view but from a practical perspective.

This is not a textbook but a guide for anyone interested in statistical, probability, and reliability to improve processes and profitability in their organizations. When you begin a study of something, you want to do it well. You want to design a good study, analyze the results properly, and prepare a cogent report that summarizes what you've found. Six Sigma and Beyond: Statistics and Probability shows you how to use statistical tools to improve your processes and give your organization the competitive edge.

Table of Contents

Statistical Concepts

Designing a Study

Counting Responses for Single Variable

Summarizing Data

Counting Responses for Combinations

Changing the Coding Scheme

Looking at Means

Means from Samples

Working with the Normal Distribution

Testing Hypothesis - Two Independent Means

Testing Hypothesis - Two Dependent Means

Testing Hypothesis about Independence

Comparing Several Means

Plotting Data


Probability Changes

Set Theory and Venn Diagrams

Probability Concepts

Discrete and Random Variables

Binomial and Poison Distributions

Continuous and Uniform Distributions

Normalizing Binomial and Central Limit Theorem

Functions of Random Variables

Exponential Distribution and Reliability

Poison Process

Chi Square Distribution

T Distribution

Sample Size for Mean Distribution

Sampling Theory

Probability Plots and Percentiles

Reliability Concepts

Failure Rates

Reliability Rate




Weibull Distribution

Gamma Distribution and Reliability

Hypothesis Testing and OC Curves

Least Squares and Regression Analysis

Taylor Series Expansion

Subject Categories

BISAC Subject Codes/Headings:
BUSINESS & ECONOMICS / Quality Control