{domain:"www.qualitydigest.com",server:"169.47.211.87"} Skip to main content

        
User account menu
Main navigation
  • Topics
    • Customer Care
    • Regulated Industries
    • Research & Tech
    • Quality Improvement Tools
    • People Management
    • Metrology
    • Manufacturing
    • Roadshow
    • QMS & Standards
    • Statistical Methods
    • Resource Management
  • Videos/Webinars
    • All videos
    • Product Demos
    • Webinars
  • Advertise
    • Advertise
    • Submit B2B Press Release
    • Write for us
  • Metrology Hub
  • Training
  • Subscribe
  • Log in
Mobile Menu
  • Home
  • Topics
    • Customer Care
    • Regulated Industries
    • Research & Tech
    • Quality Improvement Tools
    • People Management
    • Metrology
    • Manufacturing
    • Roadshow
    • QMS & Standards
    • Statistical Methods
    • Supply Chain
    • Resource Management
  • Login / Subscribe
  • More...
    • All Features
    • All News
    • All Videos
    • Contact
    • Training

All Features

Does C = 0 Sampling Really Save Money?
John Flaig
The claim is made and widely believed that C = 0 sampling plans are more cost effective than classic sampling plans such as ANSI/ASQ Z1.4. Below is a preliminary analysis of the cost difference between the two sampling plans using the hypergeometric probability distribution to compare a Squeglia C…
A Mommy’s Look at Lyme Disease Statistics
Dawn Keller
I spend the majority of my time entrenched in statistics. Using statistics. Studying statistics. Developing and testing statistical software. Statistics guide many of my decisions at work and in life. That’s the world of an engineer. For this reason, you can imagine my surprise when my husband…
The Risks in Root Cause Analysis
John Flaig
What’s wrong with root cause analysis? Let’s begin with the name, which is singular. It implies that there is only one root cause, when in reality most problems are usually caused by a complex combination of several factors, some of which are more significant than others. To appreciate this point…
Problems With Skewness and Kurtosis,
Part 2
Donald J. Wheeler
In part one we found that the skewness and kurtosis parameters characterize the tails of a probability model rather than the central portion, and that because of this, probability models with the same shape parameters will only be similar in overall shape, not identical. However, since software…

Pagination

  • First page « First
  • Previous page ‹ Previous
  • …
  • Page 10
  • Page 11
  • Page 12
  • Page 13
  • Page 14
  • Page 15
  • Page 16
  • Page 17
  • Current page 18

© 2026 Quality Digest. Copyright on content held by Quality Digest or by individual authors. Contact Quality Digest for reprint information.
“Quality Digest" is a trademark owned by Quality Circle Institute Inc.

footer
  • Home
  • Print QD: 1995-2008
  • Print QD: 2008-2009
  • Videos
  • Privacy Policy
  • Write for us
footer second menu
  • Subscribe to Quality Digest
  • About Us
  • Contact Us