Improvement Insights Blog

To P or Not to P

Most Six Sigma statistics rely on p values. But statisticians have been raising alarm about the problems with p values. Here’s what’s going on:



“Hi, I’m Jay Arthur, author of “Lean Six Sigma For Hospitals” and the QI Macros [software].

“I get these emails about different courses that are being offered (I think one on Coursera) but it was one on statistics and it was “To P or Not to P That is the Question.”

“Have you been watching anything in the statistics world? Statisticians think that P values can be misleading and potentially dangerous.

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Posted by Jay Arthur in Improvement Insights, Jay Arthur Blog.

p value’s Dirty Little Secret

The American Statistical Association (ASA) has issued a statement about statistical significance and  p values.  It quotes ScienceNews article from 2010: “It’s science’s dirtiest secret: The ‘scientific
method’ of testing hypotheses by statistical analysis stands on a flimsy foundation.”

Six Sigma spends a lot of time on hypothesis testing using p values, but our use of p values may lack the rigor required. The ASA states: By itself, a p-value does not provide a good measure of evidence regarding a model or hypothesis.

Continue Reading "p value’s Dirty Little Secret"

Posted by Jay Arthur in Six Sigma.