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Category >> Control charts (created
2007-06-11). |

A control chart is a graphical tool used in many industrial settings that monitors a work process on a continual and on-going basis. Articles are arranged by date with the most recent entries at the top. Also see Category: Analysis of means, Category: Adverse events in clinical trials, or Category: Quality control. You can find outside resources at the bottom of this page.

**2008**

[[There is no material yet from my new site.]]

- Advanced Topics in Statistical
Process Control: The Power of Shewhart's Charts Description:
*Wheeler's book provides theoretical and empirical justification for the use of control charts. A lot of good material if you need to justify why you are using a certain approach for control charts. This book is for students who want more mathematical details.* - Building Continual Improvement: A
Guide for Business Description:
*Wheeler and Poling's book provides a simple but rigorous introduction and overview of the use of control charts. This book is a gentle introduction to a specialized topic.* - Innovative Control Charting: Practical SPC Solutions for Today's Manfacturing Environment
- Rip Stauffer.
**Some Problems with Attribute Charts | Quality Digest**.*Excerpt: "While p- and np- charts can be very useful, and I highly recommend them when the conditions are correct, they aren't always the best charts to use, and should be used with some caution. There are a few inherent problems that seem to crop up a lot. This article will illustrate a couple of the foibles observed over many years of wrangling with these interesting charts."*[Accessed April 5, 2010]. Available at: http://www.qualitydigest.com/inside/quality-insider-article/some-problems-attribute-charts.html - SPC for the Rest of Us: A Personal Path to Statistical Control
- Understanding Statistical
Process Control. Description:
*Donald Wheeler and David Chambers provide all the details for someone who uses control charts on a regular basis. They offer lots of practical advice. This book is a gentle introduction to a specialized topic.* - Understanding Variation: The Key to Managing Chaos

All of the material above this paragraph is licensed under a Creative Commons Attribution 3.0 United States License. This page was written by Steve Simon and was last modified on 2010-04-11. The material below this paragraph links to my old website, StATS. Although I wrote all of the material listed below, my ex-employer, Children's Mercy Hospital, has claimed copyright ownership of this material. The brief excerpts shown here are included under the fair use provisions of U.S. Copyright laws.

**2007**

11. Stats: The pros and cons of control charts versus data mining (November 17, 2007). In a talk I gave in December 2006, I highlighted how in the analysis of adverse event data, control charts can augment more complex statistical tools like data mining. Here's a summary of the pros and cons of using control charts. [[The file, ProsControlCharts.html, has been misplaced.]]

10. Stats: Common sources of confusion in a class on quality control (August 22, 2007). I presented a training class, Stats #18: Quality Control: A Hands-On Workshop, for the American Society for Andrology. The major emphasis was on the computation of control charts. It's always interesting to see how this material goes over.

9. Stats: Calculating a P control chart (March 7, 2007). If you are collecting data on proportions with a consistent denominator for each proportion, then you can plot this data on a control chart. This type of chart is called a P chart and it is very simple to calculate.

8. Stats: P control chart, answers to on your own exercises (March 7, 2007). On the web page Stats: Calculating a P control chart (March 7, 2007) you were asked to calculate P charts for two data sets.

7. Stats: Calculating an XBAR-S control chart (March 2, 2007). The following data represents a weekly evaluation of vaccine potency. The data is taken from

An adaptation of quality control chart methods to bacterial vaccine potency testing.H. C. Batson, M. Brown, M. Oberstein. J Bacteriol 1951: 61(4); 407-19, but I have taken some liberties with the data to simplify the calculations. Each week, three lots of vaccine are tested for potency. Calculate a control chart for this data.6. Stats: XBAR-S control chart, answers to on your own exercise (March 2, 2007). On the web page Stats: Calculating an XBAR-S control chart (March 2, 2007) you were asked to calculate an XBAR-S control chart.

5. 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).

**2006**

4. Stats: Unusual advice about control charts (December 18, 2006). Someone sent me some recommended guidance on how to use a control chart and it included the following quote: "

Do not correct the process if the out-of-control values can be shown to be due to chance failure when process is actually in control (special cause variation)." I'm probably taking this quote out of context, but it is a rather unusual claim.3. Stats: Applications of the CUSUM chart (June 20, 2006). I am interested in investigating the use of CUSUM charts in monitoring accrual rates, drop out rates, and adverse event rates in a clinical trial. Some references which I might cite in a literature review are listed here.

2. Stats: Learning more about control charts (February 1, 2006). Someone asked me about resources for learning how to use control charts.

**2000**

1. Stats: Sigma in the control chart (January 27, 2000).

Dear Professor Mean: I ran a control chart in SPSS for individual values, and the control limits don't correspond with what I would expect from the descriptive procedure that I ran first. In particular, the value of sigma in the control chart appears to be an approximation of what I computed earlier. Why would SPSS use a different calculation for sigma?

- Definition: Common cause of variation
- Definition: Control chart
- Definition: Special cause of variation

**What now?**

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This work is licensed under a Creative Commons Attribution 3.0 United States License. This page was written by Steve Simon and was last modified on 2010-04-11.