Quality and manufacturing practitioners are most familiar with the effect of variation on product quality, and this is still the focus of the quality management and Six Sigma bodies of knowledge.

The ultimate purpose for collecting data is to take action. In some cases the action taken will depend upon a description of what is at hand. In others the action taken will depend upon a prediction of what will be.

A few months back, I was reading a really good article from The Wall Street Journal, titled “Stop Using Excel, Finance Chiefs Tel

The phrase, “Are we there yet?” has long been associated with boring summer road trips. However, a new study shatters that myth, as it shows that 69 percent of people say traveling to their destination is often as fun as the actual vacation destination.

I have written about sample size calculations many times before.

I recently got hold of the set of data shown in figure 1. What can be done to analyze and make sense of these 65 data values is the theme of this article. Read on to see what is exceptional about these data, not only statistically speaking.

The Atlantic hurricane season is now upon us, and the National Oceanic and Atmospheric Administration (NOAA) has just released its 2018 seasonal hurricane outlook which calls for a slightly above average season.

Quality is related to processes.

Confidence intervals show the range of values we can be fairly, well, confident, that our true value lies in, and they are very important to any quality practitioner. I could be 95-percent confident the volume of a can of soup will be 390–410 ml.

A lot of people in my classes struggle with conditional probability. Don’t feel alone, though. A lot of people get this (and simple probability, for that matter) wrong.