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

User account menu
Main navigation
  • Topics
    • Customer Care
    • FDA Compliance
    • Healthcare
    • Innovation
    • Lean
    • Management
    • Metrology
    • Operations
    • Risk Management
    • Six Sigma
    • Standards
    • Statistics
    • Supply Chain
    • Sustainability
    • Training
  • 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
    • 3D Metrology-CMSC
    • Customer Care
    • FDA Compliance
    • Healthcare
    • Innovation
    • Lean
    • Management
    • Metrology
    • Operations
    • Risk Management
    • Six Sigma
    • Standards
    • Statistics
    • Supply Chain
    • Sustainability
    • Training
  • Login / Subscribe
  • More...
    • All Features
    • All News
    • All Videos
    • Contact
    • Training

Analysis Using Few Data, Part 1

Some of these batches are not like the others…

Donald J. Wheeler
Mon, 06/04/2012 - 13:06
  • Comment
  • RSS

Social Sharing block

  • Print
  • Add new comment
Body

Editor--Part 2 of this article can be found here.

In some industries a few test batches will be produced prior to going into production. When this happens, a critical question is: “Are all of the test batches alike?” With only one value per batch, how can we compare a set of three or more values to see if one of the values is different from the others? This article will provide an answer by presenting a new test for homogeneity.

ADVERTISEMENT

The problem here is substantially different from most of the problems addressed by statistical tests. Here we will want to use the test batches to characterize future production, but before we can meaningfully interpret even the simplest statistics in this way, we will need homogeneity between the test batches.

 …

Want to continue?
Log in or create a FREE account.
Enter your username or email address
Enter the password that accompanies your username.
By logging in you agree to receive communication from Quality Digest. Privacy Policy.
Create a FREE account
Forgot My Password

Comments

Submitted by willy@qsconsult.be on Thu, 06/07/2012 - 02:46

Question on chunky W ratios

Thanks for a very interesting article. My question relates to the statement just above example 2: "...we prefer for M to be at least 20." I understand the reasoning to state this, but off course it is something that the experimenter cannot influence. You get the data that you get from the process. Does this mean that if M < 20, due to the chunkiness of the W ratios, the test should not be used? Is there an alternative in that case.

Kind regards,

Willy Vandenbrande

 

  • Reply

Add new comment

Image CAPTCHA
Enter the characters shown in the image.
Please login to comment.
      

© 2025 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