Talk:Control chart

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This article should not be merged. Control charts are a related but very clearly separate issue from the common and special causes from which they arise. -- Phil 20:39, 14 December 2005 (UTC)

Other control charts besides Shewhart ones

Shewhart charts are most common in control charting because of their relative simplicity (over other charts), and therefore are an excellent jumping off point. However, there are control charts (CUSUM, EWMA, and multivariate forms of CUSUM, EWMA, and Shewhart charts) which differ considerably from the basic rules being introduced here. The article in its present form is very much targeted to Shewhart control charts and overlooks the fact that there are other types of control charts which also test to see whether a process mean or variance has shifted. Significant amounts of information need to be added to this article, and I envision much of the content presently in this one moving to a new article titled Shewhart control charts. I am going to try to add a little bit to this article to get it started. --Statwizard 15:03, 23 March 2006 (UTC)

Real-time contrasts chart

I have located a copy of the paper introducing real-time contrasts (RTC) on ResearchGate. In this paper, the authors state that "the control limit UCL is selected so that ARL0 is approximately 200," which is consistent with the statement in this article that the RTC chart "detect[s] smaller changes more efficiently." It seems that this statement could be cleaned up in this Wikipedia article, but I am unsure how best to incorporate this into the article. Any suggestions? Tom Hopper (talk) 15:42, 17 January 2014 (UTC)

Veracity and Lack of Citation

"While Dr. Shewhart drew from pure mathematical statistical theories, he understood data from physical processes typically produce a "normal distribution curve" (a Gaussian distribution, also commonly referred to as a "bell curve"). "

This should be taken out, unless there is a specific citation for proposition that "he understood" what is being claimed. On the face of it is wrong because normality isn't required to use a control chart, and because its not actually true, e.g. any process which is "not in statistical control" is de facto not a normal distribution!69.250.186.253 (talk) —Preceding undated comment added 14:10, 4 May 2012 (UTC).

A process can be perfectly normal and out of statistical control if it excedes both of the desired limits defining control range. Example, pH data excedes upper and lower limits by the same degree and an even number of times. Either way, not sure comment is critical to scope of this article. Joe Jirka (talk) 18:07, 26 December 2012 (UTC)

I question the wording that "application of the charts in the presence of such [non normality] increases the... type I and type II error rates of the control charts." Having a limit off one way or the other can never increase both type II and type I. I suppose the opposite end of the distribution may experience a Type II crisis, whenever the extreme tail end experiences a Type I crisis. This could be clarified as "type I or type II" and then a sentence added that eliminates some head scratching by the reader. — Preceding unsigned comment added by 144.15.255.227 (talk) 19:58, 22 February 2013 (UTC)

Shewhart set 3-sigma (3-standard error) limits on the following basis

Shewhart set 3-sigma (3-standard error) limits on the following basis

Didn't he actually do empirical experiments. I.e. he drew chips from a bowl.

So shouldn't there be a fourth bullet something like: experimentation

68.55.60.111 (talk) 11:24, 2 May 2013 (UTC)