Fourteen years ago, I published “Do You Have Leptokurtophobia?” Based on the reaction to that column, the message was needed.

Data overload has become a common malady. Modern data collection technologies and low-cost database storage have motivated companies to collect data on almost everything. The result? Data overload.

We are one year away from the 100th anniversary of the creation of the control chart: Walter Shewhart created the control chart in 1924 as an aid to Western Electric’s manufacturing operations.

In last month’s column, we looked at how process-hyphen-control algorithms work with a process that is subject to occasional upsets.

Today’s manufacturing systems have become more automated, data-driven, and sophisticated than ever before.

Many articles and some textbooks describe process behavior charts as a manual technique for keeping a process on target.

As we learned last month, the precision to tolerance ratio is a trigonometric function multiplied by a scalar constant. This means that it should never be interpreted as a proportion or percentage.

The keys to effective process behavior charts are rational sampling and rational subgrouping. As implied by the word rational, we must use our knowledge of the context to collect and organize data in a way that answers the interesting questions.

Continuing our thinking about ways for data leaders to save money during a recession, this article drills into saving on your data usage

As the foundations of modern science were being laid, the need for a model for the uncertainty in a measurement became apparent. Here we look at the development of the theory of measurement error and discover its consequences.