Category: Analysis of means (ANOM) (June 18, 2007). Analysis of means (ANOM) is an approach used in quality control circles to compare averages, proportions, or counts across several groups. Articles are arranged by date with the most recent entries at the top. You can find the theme and closely related categories and other resources at the bottom of this page.

Stats: What I'm working on right now (March 18, 2007). There are several research projects where I am actively looking for collaborators. I thought I'd outline these topics briefly here.

Stats: Calculation of Analysis of Means limits (March 6, 2007). This page shows some of the details for calculating an analysis of means (ANOM) chart.

Stats: Analysis of Means answers to "on your own" exercises (March 6, 2007). On the web page Stats: Calculation of Analysis of Means limits (March 6, 2007) you were asked to calculate ANOM charts for two different data sets.

Stats: ANOM table for alpha=0.05, part 1 (March 4, 2007). Here's a table of critical values for analysis of means (ANOM) at an alpha level of 0.05.

Stats: Analysis of Means calculations (March 2, 2007). Analysis of Means (ANOM) are available for a wide range of data sets, and it is impossible to summarize all the applications of ANOM here. The goal on this web page is to illustrate a few of the calculations.

Stats: Team exercise to illustrate ANOM calculations (February 28, 2007). I am in charge of a workshop for the American Society for Andrology for their 32nd Annual Conference in Tampa Florida. This society holds a laboratory workshop every year, and this year, it is being split into two workshops: Sperm Morphology -A Hands-On Workshop, from 8am to 11:30am, and Quality Control -A Hands-On Workshop, from 1:30pm to 4:30pm. I will be teaching the afternoon workshop along with Dr. Steven Schrader. Some brief details about both classes are on the web: a preliminary schedule, a flier in PDF format, and a brochure in PDF format.

Stats: When is a control chart not a control chart? (February 6, 2007). I found a pair of data sets on the web that represent counts and where one goal of the data collection is to see if any of the individual counts differ from the overall average. They look quite similar and you might be tempted to analyze both of them using a control chart. But the second example is different in subtle, but important ways and it is better analyzed using an approach called Analysis of Means (ANOM).

Stats: Some resources for Analysis of Means (June 30, 2006). (updated February 1, 2007) 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.

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This webpage was written by Steve Simon and was last modified on 07/08/2008.