Caught in the Draft

In December of 1969, the Selective Service held a lottery to determine the order in which young men would be called up for the Draft.  My number was a low 53, and that set the course for much of my adult life.  Turns out, the odds were against me.



  • Want to run more analyses? This article from the Journal of Statistics Education shows the way.



You can teach yourself

Tara Westover gives the Big Reveal about education

My parents would say to me all the time: you can teach yourself anything better than someone else can teach it to you. Which I really think is true. I hate the the word “disempower,” because it seems kind of cliché, but I do think that we take people’s ability to self-teach away by creating this idea that that someone else has to do this for you, that you have to take a course, you have to do it in some formal way.

It took me a long time to learn that you take courses to find out what you don’t know, so you can go study up on it, and organize your self-study.

Tip from Joanne Jacobs, who I’ve neglected lately.

Feynman’s 4-Step Learning Process


From the man who showed up rocket scientists, a simple checklist:

  • pick a topic you want to understand and start studying it
  • pretend to teach your topic to a classroom*
  • go back to the books when you get stuck**
  • simplify and use analogies

Exactly the technique I use to “get smart” on lots of stuff I should know, but don’t.

Tip from Old Remus at the Woodpile Report (report #553).

*Pretend, hell!  Wiggle that topic into your course syllabus, and commit yourself to teaching it.  Nothing sharpens your studies like trying to create a coherent lecture.  Or two.  With a supporting homework assignment.  And quiz or exam questions.

**There are gurus out there, go talk to them.  I’m lucky to work at a university, where many are right down the hall.  I have yet to meet an expert unwilling to speak about his area of expertise.  Often at great, nay overwhelming, length.

Ooo, ooo! I have a better idea!

Those wily Brits have identified some major stumbling blocks in their education system:

Schools are removing analogue clocks from examination halls because teenagers are unable to tell the time, a head teachers’ union has said.

Teachers are now installing digital devices after pupils sitting their GCSE and A-level exams complained that they were struggling to read the correct time on an analogue clock.


It gets worse

Earlier this year, a senior paediatric doctor warned that children are increasingly finding it hard to hold pens and pencils because of an excessive use of technology. …”It’s easier to give a child an iPad than encouraging them to do muscle-building play such as building blocks, cutting and sticking, or pulling toys and ropes. Because of this, they’re not developing the underlying foundation skills they need to grip and hold a pencil.”

My remedy?  Establish some simple prerequisities: if you can’t hold the pencil, or read the analog clock, you fail the exam.

What a bunch of lightweights.

Tip from the GeekPress.

When all you have is a hammer…

…everything looks like a nail.

Daniel Lakens, the 20% Statistician, takes a rare but easy shot at statisticians and null hypothesis significance testing.

Our statistics education turns a blind eye to training people how to ask a good question. After a brief explanation of what a mean is, and a pit-stop at the normal distribution, we jump through as many tests as we can fit in the number of weeks we are teaching. We are training students to perform tests, but not to ask questions

He defines

…the Statisticians’ Fallacy: Statisticians who tell you ‘what you really want to know’, instead of explaining how to ask one specific kind of question from your data.

My favorite is the two-tailed test of the difference of two means, which can provide evidence that the two are different, but not that they are (nearly) the same.  My runners up are goodness-of-fit tests, which do no such thing.  Sometimes I feel like I’m selling the researcher’s version of Snake Oil, rather than teaching sound data analysis and interpretation.

Lakens closes with an excellent addendum, a reference to David Hand’s Deconstructing Statistical Questions,  which goes into much more detail.

Seven Pillars

Wisdom hath built her house, she hath hewn out her seven pillars.  –Proverbs 9:1

I just finished Stephen Stigler’s The Seven Pillars of Statistical Wisdom, and I’m daunted–and embarrassed that I waited so long to read it.  Stigler gives us a structure and taxonomy to statistical thinking* that gives us the “big picture” of statistics.


Quite a difference from the descriptives-to-inference-to-models approach that most textbook authors follow.  This is making me rethink how I approach my introductory courses, especially those for statistics majors.  I’m starting with a baby step: adding the (inexpensive, paperbound) book as a required reading in my statistical research methods class.

*the 7 pillars: aggregation, information, likelihood, intercomparison, regression, design, and residual (and that’s just the table of contents!)