Posts Tagged misuse of statistics
Over half of all children have below-average reading skills
Posted by mark in Education, leadership, pop, Uncategorized on June 24, 2019
Yes, you read that right—this statistic was cited by Eugenia Cheng last weekend in her column for the Wall Street Journal on why Averages Aren’t Always What They Seem. In this case, a small number of excellent readers skews the distribution to the right.
But none of this applies to my offspring, them being in the Lake Wobegon region where all the children are above average.
I would never admit it, but deep down I realize that I’ve succumbed to the superiority illusion, aka the Dunning-Kruger effect. As advised in this June 3rd post by Forbes you’d best be careful not to be taken in by individuals who consistently overestimate their competence due to this cognitive bias.
Steve Carell took the superiority illusion to an absurd extreme as the manager Michael Scott in the “The Office” television series. It’s funny unless you are subject to someone like this.
“The knowledge and intelligence that are required to be good at a task are often the same qualities needed to recognize that one is not good at that task—and if one lacks such knowledge and intelligence, one remains ignorant that one is not good at that task.”
— David Dunning, professor of psychology at the University of Michigan
“Stupid people are so stupid they’re unable to grasp the fact that they’re stupid.”
— Letter to Editor of Oroville Mercury Register, 6/23/19
ASA calls for abandoning the declaration of results being “statistically significant”
Posted by mark in Basic stats & math, Uncategorized on May 1, 2019
On March 21 the American Statistical Association (ASA) sent out a shocking email to all members that the lead editorial in a special, open-access issue of The American Statistician calls for abandoning the use of “statistically significant”. With irony evidently intended by their italicization, they proclaimed it “a significant day in the history of the ASA and statistics.
I think the probability of experimenters ignoring ASA’s advice and continuing to say “statistically significant” approaches 100 percent. Out of the myriad of suggestions in the 43 articles of The American Statistician special issue the ones I like best come from statisticians Daniel J. Benjamin and James O. Berger. They propose that, because “p-values are often misinterpreted in ways that lead to overstating the evidence against the null hypothesis”, the threshold for “statistical significance” of novel discoveries require a threshold of 0.005. By their reckoning, a p-value between 0.05 and 0.005 should the be degraded to “suggestive,” rather than “significant.”*
It’s a shame that p-hackers, skewered in this xkcd cartoon, undermined the sound application of statistics for filtering out findings unsupported by the data.
*The American Statistician, 2019, Vol. 73, No. S1, 186–191: Statistical Inference in the 21st Century, “Three Recommendations for Improving the Use of p-Values”.
“Decisions taken by statistical professionals are final”
I’m just catching up on the Wall Street Journal issues that accumulated while I attended a statistical conference and then co-taught a workshop on Designed Experiments for Life Sciences. A June 3rd article by WSJs “Numbers Guy” Carl Bialik caught my eye with a graphic showing that most UK citizens distrust official statistics. This caused their government to create a Statistics Authority that will police other agencies on the numbers they release to the public. Here some key points as reported at this UK government web site:
So it seems that the number nerds will rule after all — just like they always dreamed when being belittled by the bullies who thought math and stats were simply a waste of time. Statisticians rule!