{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

Why Use Ranges?

What they didn’t teach in your stat class

Donald J. Wheeler

SPC Press

Mon, 02/03/2014 - 16:29
  • Comment
  • RSS

Social Sharing block

  • Print
Body

Last month in “The Analysis of Experimental Data,” I presented a method for analyzing experimental data that was built on the use of the range statistic as a measure of dispersion. In this day of computers and software, why should we even consider using ranges in our analysis of experimental data? Wouldn’t other, more efficient measures of dispersion do a better job? Since these questions can be a barrier to the effective analysis of data, they deserve to be answered.

ADVERTISEMENT

 …

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
Top Stories
Beyond the Statistics: Implementing the New VDA AIAG SPC Manual
Multivariate Charts
All Whys Are Not The Same
Flying Blind: What Your Quality Data Miss Every Shift
Book Preview
The Psychology of AI Adoption at Work

Comments

Submitted by Steve Moore on Wed, 02/05/2014 - 13:21

History

Dr. Wheeler, I have always been fascinated by the history of statistics - where things came from. "The Lady tasting Tea", of course, comes to mind. Thanks for the historical perspective you provided in this and many other of your writings.
  • Reply

Add new comment

Please login to comment.

© 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