Recently, I’ve had a sad, increasing sense of déjà vu. Twitter has become even more vacuous, and LinkedIn has quickly devolved into a business version of Facebook.

In Parts One and Two we defined the equivalence of in

When I first learned quality improvement back in 1989 at Florida Power and Light, the consultants who trained us taught a very specific way to draw a Pareto chart.

Current business conversation often focuses on data and big data. Data are the raw information from which statistics are created and provide an interpretation and summary of data.

Anthony Chirico¹ describes how narrow-limit gauging (NLG, aka compressed limit plans) can reduce enormously the required sample size, and therefore the inspection cost, of a traditional attribute sampling plan.

Now, if you’re familiar with either statistics or J.R.R. Tolkien, I know the title grabbed your attention.

Last month we provided an operational definition of when measurement systems are equivalent in terms of bias.

Ever since sportswriter Henry Chadwick popularized the box score in the 19th century, baseball fans have had a love affair with statistics.

As soon as we have two or more instruments for measuring the same property the question of equivalence raises its head. This paper provides an operational definition of when two or more instruments are equivalent in practice. 

In most healthcare settings, workers attend weekly, monthly, or quarterly meetings where performances are reported, analyzed, and compared to goals in an effort to identify trends.