Stamatis D.H. Essential Statistical Concepts for the Quality Professional

CRC Press, 2012. — 504 p. — ISBN10: 1439894574.The essence of any root cause analysis in our modern quality thinking is to go beyond the actual problem. This means not only do we have to fix the problem at hand but we also have to identify why the failure occurred and what was the opportunity to apply the appropriate knowledge to avoid the problem in the future. Essential Statistical Concepts for the Quality Professional offers a new non-technical statistical approach to quality for effective improvement and productivity by focusing on very specific and fundamental methodologies and tools for the future.
Written by an expert with more than 30 years of experience in management, quality training, and consulting, the book examines the fundamentals of statistical understanding, and by doing so demonstrates the importance of using statistics in the decision making process. The author points out pitfalls to keep in mind when undertaking an experiment for improvement and explains how to use statistics in improvement endeavors. He discusses data interpretation, common tests and confidence intervals, and how to plan experiments for improvement. The book expands the notion of experimentation by dealing with mathematical models such as regression to optimize the improvement and understand the relationship between several factors. It emphasizes the need for sampling and introduces specific techniques to make sure accuracy and precision of the data is appropriate and applicable for the study at hand.Tests and Confidence Intervals for Means
Tests and Confidence Intervals for Standard Deviations
Understanding and Planning the Experiment and Analysis of Variance
Typical Sampling Techniques
Understanding Computer Programs for Design and Estimating Design Power
Appendixes
Minitab Computer Usage
Formulas Based on Statistical Categories
General Statistical Formulas
Hypothesis Testing Roadmap
Test Indicators
Hypothesis Testing—Selected Explanations and Examples
When to Use Quality Tools—A Selected List