Management requires prediction. However, when making predictions it is easy to torture the data until they surrender and tell you what you expect to hear.

Editor’s note: The following is from a transcript of a forgotten speech given in Tokyo in 1978 by W. Edwards Deming for the Union of Japanese Scientists and Engineers (JUSE). Because the original was a poor photocopy, there are small portions of text that could not be transcribed.

One of the most common questions about any production process is, “What is the fraction nonconforming?” Many different approaches have been used to answer this question.

In this year’s April issue of the Bridge Bulletin, the ACBL (American Contract Bridge League) unveiled a new logo as part of a rebranding campaign to promote the beloved game of bridge to a wider audience.

First, let it be known that all charts for count-based data are charts for individual values. Regardless of whether we are working with a count or a rate, we obtain one value per time period and want to plot a point every time we get a value.

There are many control chart rules to detect special causes (i.e., out-of-control conditions). Although most of these rules are clear, the one that seems to befuddle most people is the rule about trends.

What do the shape statistics known as skewness and kurtosis tell us about our data? Last month we saw how the average and standard deviation define the balance point and radius of gyration for our data.

Part one of this article showed that it is possible, by means of a Visual Basic for Applications program in Microsoft Excel, to calculate the fraction of in-sp

IATF 16949:2016 clause 7.1.5.1.1 requires measurement systems analysis (MSA) to quantify gage and instrument variation. The deliverables of the generally accepted procedure are the repeatability or equipment variation, and the reproducibility or appraiser variation.