StATS: Some resources for Analysis of Means (created 2006-06-30, updated 2007-02-01)
One of the techniques recommended by Davis Balestracci when he visited CMH in June 2006 was Analysis of Means, which often is abbreviated ANOM. You can use ANOM much like a control chart, but it is applied when you have a collection of averages representing the performance of specific subgroups. The classic application is examining the performance of several different workers who are all performing a similar task. I tend to dislike examples like that because it implies that the root cause of most problems lies in the workers themselves. That's not really true, though, but even if it were, such a focus early on in a quality program would lead to a lot of resistance, defensiveness, and possibly even fudging the numbers.
Still, ANOM is a useful tool that has a lot of profitable applications.
The first thing you might notice is the similarity between the acronym ANOM and another acronym, ANOVA (Analysis of Variance). The two approaches can be used on the same problem, but they have a different focus. In ANOVA, the comparison is typically to see if certain levels of a factor differ from other levels of a factor. In ANOM, the comparison is typically to see if certain levels of a factor differ from the overall mean. You can adapt ANOVA to perform the latter task, but it is typically not done all that often. The other difference is that ANOM will typically use a graphical display that looks much like a control chart.
Here is a nice resource for ANOM
A brief tutorial for ANOM is available at
that shows how to use MINITAB for ANOM. Most software programs do not have ANOM. (I know for sure that R, SPSS, and STATA do not have it) but instead provide the results of the ANOVA model instead. Apparently, ANOM is available in the SAS/QC package.
Donald Wheeler is one of my favorite authors, and you can find a nice discussion of ANOM in Chapter 18 of
(Update: 2007-02-01). The best book on this topic is
An interesting review of this book is on the web in PDF format at
You can find the table of contents, introduction, and first chapter of the book on the web in PDF format at
The first chapter includes several simple examples. The first example shows paint drying times for four different types of paint. The data (mean +/- sd) are
6.88 +/- 1.72
9.28 +/- 1.85
9.00 +/- 2.81
9.90 +/- 1.95
Each paint type was tested four times, for a total of 16 observations. The overall mean is 8.8 and the lower and upper decision limits are 7.0 and 10.5, respectively. When I get some time, I'd like to replicate this example using R software.
This page was written by Steve Simon while working at Children's Mercy Hospital. Although I do not hold the copyright for this material, I am reproducing it here as a service, as it is no longer available on the Children's Mercy Hospital website. Need more information? I have a page with general help resources. You can also browse for pages similar to this one at Category: Analysis of means.