Stats #18: Quality Control: A Hands-On Workshop

Content: This training class will show you how to use statistical tools to assess the quality of an on-going laboratory or medical process.

Objectives: In this class, you will learn how to:

• implement measures to identify common and special causes of variation and to reduce them,.
• perform Analysis of Means (ANOM) to compare results among a peer group, and
• discover root causes using a Fishbone diagram; and

Teaching strategies: Didactic lectures and small group exercises.

Notes: There are no pre-requisites for this class. Please bring a pocket calculator for some simple arithmetic calculations.

Web pages included in this handout:

• Where you can find this handout
• Why I don't use PowerPoint
• Practice exercises
• A plea for open-mindedness
• What is a control chart?
• What is a special cause of variation?
• What is a common cause of variation?
• Statistical Koan: The very busy tailor.
• Using a pocket calculator to compute a standard deviation
• Calculating an XBAR-S control chart
• Calculating a P chart
• Calculating an Analysis of Means chart
• Table for Analysis of Means
• Examples of a Fishbone diagram

The workshop will conclude with a summary and moderated discussion. Ample time for discussion of all topics has been allocated.

A condensed version of this handout is available at

Information about my book, Statistical Evidence in Medical Trials

Where can you find this handout?

This handout and the handouts that I use for all of my seminars and training classes are a compilation of individual web pages at www.childrensmercy.org/stats. I use the "Include Page" feature of Microsoft FrontPage to combine these into a single page. You can always find the most recent version of this compilation by going to the web address listed at the bottom of this page. Links for the handouts for other seminars and classes appear at www.childrensmercy.org/stats/training.asp.

Why don't I use PowerPoint?

I stopped using PowerPoint for my presentations in the mid 1990's. This was based on Edward Tufte's advice that presenting information in a paper handout is more effective than presenting the information on a projected screen. I found this to be excellent guidance. I enjoy talking when I don't have to wrestle with a laptop computer. I look at my audience more and interact with them better. I elaborate on this in greater detail at www.childrensmercy.org/stats/weblog2004/powerpoint.asp.

Stats #18: Practice Exercise

Form a team of four to six people. The size may be slightly bigger or smaller if the instructor agrees, but teams of size one are not teams. You will receive a packet that includes a toy and a measuring tape. Here are some examples, but your toy may be different.

 Flying saucer Toy car with "pull-back". Foam disc gun.

Please note that some of the toys are choking hazards, so take appropriate precautions if one of the members of your group is less than three years old.

 This webpage was originally published at the StATS website, which is currently unavailable. There is a dispute about the ownership of these pages, so I am only able to include a brief excerpt from this page.

[08/weblog2006/OpenMindedness.asp]
[08/training/www.childrensmercy.org/definitions/ControlChart.htm]
[08/training/www.childrensmercy.org/definitions/SpecialCause.htm]
[08/training/www.childrensmercy.org/definitions/CommonCause.htm]

The following story illustrates the problems that can occur when you fail to recognize the difference between common cause and special cause variation.

The Busy Tailor

When it was his turn to explain his recent work, Student Leaf stood up and portrayed an elegant experiment that used a central composite design with four factors. Master Stem asked, "Is this process ready for such an experiment?"

Student Leaf replied, "I do not understand."

Master Stem looked at him with an air of amusement. "If this process is not ready for an experiment, then you will make yourself very busy for no good reason."

"How can I tell, Master Stem, if a process is ready?"

"Have you computed a control chart for this process? Do you know if the process is in control?"

"I have not computed a control chart, but I do know that the process is too variable. I want to run an experiment to reduce that variation."

"I have a tailor I would like you to meet. He makes all the clothes for my family. I brought my oldest child in for a fitting and the tailor made measurements and started sewing. When I visited the next time, I had my youngest child with me. I apologized, but the tailor still insisted on doing the fitting. This required ripping out all the old seams, remeasuring and resewing. 'I am almost done with the clothes for your youngest child,' he told me, 'please come back tomorrow.' So I returned the next day, but this time I was accompanied by my middle child. 'No matter,' replied the tailor, 'I will rip out all the seams again and make the clothes fit your middle child.'"

"That is a very foolish tailor, Master Stem."

"And you, too, are foolish if you run an experiment without looking at the control chart first. If your process is out of control, that tells you that your process is not a single process, but is many instead. And you do not know which process is visiting at any time. Your experiment, carefully optimized for one process, will fit poorly for the other processes."