Posted on Categories Opinion, Rants, StatisticsTags

Kudos to Professor Andrew Gelman

Kudos to Professor Andrew Gelman for telling a great joke at his own expense:

Stupid-ass statisticians don’t know what a goddam confidence interval is.

He brilliantly burlesqued a frustrating common occurrence many people say they “have never seen happen.”

One of the pains of writing about data science is there is a (small but vocal) sub-population of statisticians jump on your first mistake (we all make errors) and then expand it into an essay on how you: known nothing, are stupid, are ignorant, are unqualified, and are evil.

I get it: many people writing about data science do not know enough statistics. However, not every person writing from a data science point of view is statistically ignorant. That is not to say computer science (my original field) doesn’t have similar problems.

Trying to destroy a sweater by pulling on a loose thread in no way establishes that it wasn’t a nice sweater in the first place (or how nice a sweater it would be if the loose thread were fixed).

(BTW: the book in question is in fact excellent. Chapter 12 alone is worth at least ten times the list price of the book.)

3 thoughts on “Kudos to Professor Andrew Gelman”

  1. I found this amazon review of Gelman’s book helpful:

    3.0 out of 5 stars
    good product with high quality.
    ByBowenon May 31, 2017
    Format: Paperback
    jimmy love it , i will come next time . arrive on time. very good . Great and affordable product. Good weight which means less pressure while cutting. Excellent ergonomic.

  2. Just a note. There is merit “to don’t feed the trolls” (i.e., don’t publicly let them get under your skin). However, at some point the community needs feedback to work on producing and promoting less trollish behavior overall. Or: “I know YOU would never do this, but how about helping shut down the person next to you who is doing this?”

  3. Funny that you mention Chapter 12. I could not agree more. I keep telling anyone interested in regression/ multi-level to read Gelman and Hill Chapter 12, and then take it from there.

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