Since the start of the Covid pandemic I have received many questions about how to analyze the Covid numbers using process behavior charts. Various schemes have been proposed and used.

With data that come along one number at a time, it is easy to get lost in the details. To see the big picture, it helps to use a time-series graph that will draw your eye in the direction that your mind wants to go.

This month I read Andy Kirk’s absorbing Data Visualisation 2, or to give it its proper title Data Visualis

Data are valuable assets, so much so that they are the world’s most valuable resource. That makes understanding the different types of data—and the role of a data scientist—more important than ever.

“With data from an epidemic there is no question of whether a change has occurred. Change is everywhere. The question is whether we are getting better or worse.

Throughout human history we’ve constantly sought out tools and capital to make us more productive. From the formation of basic tools to assist in farming to real cultivation and shaping of the land for greater yields, humankind learned to grow food.

In May 2019, James Beagle and I published an article that contained tables for the analysis of mean moving ranges or ANOMmR (pronounced a-nom-m-r). By request of those using this technique, I have expanded these tables. This article contains these expanded tables and

The daily Covid-19 pandemic values tell us how things have changed from yesterday, and give us the current totals, but they are difficult to understand simply because they are only a small piece of the puzzle.

What is quality intelligence, exactly? It’s more than marketing spin. More, even, than the sum of its many control charts. It’s not collecting data simply to further go/no-go actions.

An organization can achieve great results when everyone is working together, looking at the same information generated from the same data, and using the same rules.