The Famous DOE QuestionHow many experiments should I run?
Mon, 08/15/2016 - 00:00
I hope this little diversion into design of experiments (DOE) that I’ve explored in my last few columns has helped clarify some things that may have been confusing. Even if you don’t use DOE, there are still some good lessons about understanding… Despite 35+ Years of Evidence to the Contrary...Ingenious ways to mess up factorial designs
Mon, 07/18/2016 - 16:32
Today I want to concentrate on the foundation of what is most commonly taught as design of experiments (DOE)—factorial designs.
Elsewhere I’ve mentioned three of C.M. Hendrix’s “ways to mess up an experiment.” After 35 years of teaching DOE, I’ve… The Good News—and Bad News—About DOEThink of the principles in building a table
Thu, 06/16/2016 - 15:37
In my last column I explained how many situations have an inherent response surface, which is the “truth.” However, any experimental result represents this true response, which is unfortunately obscured by the process’s common-cause variation.… 90 Percent of DOE Is Half PlanningDon’t just teach statistics; teach how to solve problems
Wed, 05/18/2016 - 15:14
I’ve mentioned that design of experiments (DOE) is one of the few things worth salvaging from typical statistical training, and I thought I’d talk a bit more about DOE in the next couple of columns. The needed discipline for a good design is similar… Data Torturing in the Baseball World, Part 2The queasy shifting of probable, common, and special cause
Tue, 04/12/2016 - 13:07
In part one yesterday, we looked at stats of the Boston Red Sox bullpen, a typical example of baseball’s tendency to find special cause in just about anything. The Boston Globe article on which these two columns are based has been a gold mine for… Data Torturing in the Baseball World, Part 1Explaining anything as special cause
Mon, 04/11/2016 - 17:35
In honor of baseball season, I’m going to apply some simple statistical thinking to my favorite sport in a two-part series today and tomorrow. I want anyone to be able to enjoy this, so I’ll mark any technical statistics as optional reading. For… Useful Concepts From Statistics 101 and Belt Training... April fool!
Fri, 04/01/2016 - 16:19
April Fool’s Day (today) and the opening of baseball season (this Sunday) are upon us. To mark the first event, I’ll let my distinguished colleague Donald Wheeler make some eloquent and crucial statistical points that turn out to be, well,… Connecting the Big Dots to the Little Dots—Without MathAnd then follow your path of yellow-brick dots
Mon, 03/14/2016 - 18:23
This article is based on some ideas from my respected colleague Mark Hamel. Despite the lean framework, these ideas apply to any improvement approach—all of which come from the same theory, lean included.
During the past 35 years, quality has… Getting Real With Rapid-Cycle PDSAThe simplicity of smooth, upward, linear progress is a myth
Tue, 02/16/2016 - 15:22
Marketers are relentless in their efforts to seduce you with fancy tools, acronyms, Japanese terminology—and promises—about their versions of formal improvement structures such as Six Sigma, lean, lean Six Sigma, or the Toyota Production System,… Resolution for 2016: SimplifySome questions to ask in the age of excess everything
Tue, 01/26/2016 - 11:21
As I was preparing this column, one of my resources referred to chapter 48 of the 2,500-year-old Tao te Ching (quoted below), which, as some of you know, is one of my favorite sources of wisdom. It really tied today’s message together, and I hope…
