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• Exploratory Data Analysis
• Designed Experiments • Interrelationship Digraphs • Study Cause and Effect • Analyze Common Cause Variation • Process Improvement • Process Capability Indices • Rosen Yield Example • Hoerl-Snee Strategy • Is–Is Not Analysis • Cause and Effect Diagram • Pareto Chart • Flowchart • Special Cause • Basic Concepts • History • Six Sigma
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Statistical Thinking to Improve Quality
This blog examines the use of data analyses and statistical tools in a framework of statistical thinking to improve quality. The following principles form the basis for statistical thinking:
* All work occurs in a system of interconnected processes, * Variation exists in all processes, and * Understanding and reducing variation are keys to success. Statistical thinking significantly improves the effectiveness of data analyses and statistical tools.
Observations Based on the Customer-Complaint-Process Example
Posted by:
Gordon Clark on
November 3, 2009 at
7:22PM CST
The previous blog post describes an application of Statistical Thinking to increase customer satisfaction by examining the processes starting with the raw material supplier and ending with the customer use of the product. This example illustrates important features of Statistical Thinking described by Britz, Emerling et al (2000). These features include:
References
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