Friday, March 3, 2017

You aren't qualified to be a professional journalist

Just a quick thought: I'm at the 2017 CAR conference these days. I'll be talking about communicating uncertainty with Mark Hansen and Jen Christiansen. I've put together this folder with readings and our slides, in case you're curious.

Anyway, I've just attended a panel with Reveal's Jennifer LaFleur and NBC's Ronald Campbell on how to spread data literacy in news organizations. They gave some very good suggestions, but some things they said were quite worrying. For instance, when asked during the Q/A, they estimated that four out of five of the reporters and editors they regularly train aren't able to even calculate percentage change.

Let me be blunt here: If your level of numeracy is so abysmal, you aren't qualified to be a professional journalist. I know it may hurt to read this, but it's the truth. Nobody who lacks a working understanding of math, statistics, and scientific reasoning can properly inform the public. Not knowing such basic stuff is the equivalent of being unable to write coherent sentences.

We've all faced this problem —I forgot too much math in college myself!— and the solution isn't to deny that it's a problem indeed, but to solve it quickly. Get to work. Right away. Stop with the I'm-not-good-at-Math bullshit. This isn't magic, and it certainly isn't knowledge that should belong to specialized teams in a newsrooms.

Here are some books to get you started, sorted from basic to more advanced; these, and many others, informed my own The Truthful Art:


  1. Studying math or statistics is too big of a chore. Just play around with basic combinatorics on letters and binomial distribution. Can read a resampling / bootstrapping paper if you want to go further.

  2. For communicating uncertainty: I like

    - using only the sig-figs that are within theoretical 99% confidence bounds
    - printing who was asked (eg 1,000 random phone calls = 250 in northwest)
    - always using ranges, never exact figures
    - messing with font / opacity / display of handle vs stem, if it doesn't look too ugly

    But. None of this really deals with the most important issue, which is sampling people from different statistical populations. That won't show up in any numbers (unless you know the sample variance / sample kurtosis /etc should be higher than it is. which--how would you know?)


    I recently began a blog, for instances of articles where the conclusion is reversed if one takes into account even the theoretical S.E.