{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

Autocorrelated Data

What does autocorrelation tell you about your process?

Credit: Richard Carter

Donald J. Wheeler
Mon, 08/07/2017 - 12:03
  • Comment
  • RSS

Social Sharing block

  • Print
Body

Last month I mentioned that we can put autocorrelated data on a process behavior chart. But what is autocorrelated data and what does it tell us about our processes? This article will use examples to answer both of these questions.

Autocorrelation (aka serial correlation) describes how the values in a time series are correlated with other values from that same time series. The most interesting form of autocorrelation is the lag 1 autocorrelation, which describes how successive values are correlated with each other. This article will focus exclusively on lag 1 autocorrelation.

For our first example we will use the residual viscosities from a distillation column. The first 10 values, in units of stokes, are 473, 450, 464, 459, 450, 462, 481, 456, 451, and 447. The average is 459.3 and the average moving range is 12.89. The XmR chart for these data is shown in figure 1. These 10 values are reasonably homogeneous and contain no apparent signals of a change in the operation of the distillation column.

Figure 1: XmR chart for residual viscosities for periods 1 to 10

Since autocorrelation is concerned with pairs of points we begin by using these 10 successive values to define nine pairs of points:

 …

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

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