Good Statistical Writing

(Disclaimer: these are preliminary, "stream of consciousness" thoughts. I may completely change my mind after further thought.)

When I think of good writing in journalism, I usually think about a profile in The New Yorker: a piece that is entertaining, informative, and factual.

But how to write "good statistical writing"? I have found a page from UCLA [archived] about statistical writing, but appears to be geared for presenting research to a more academic (or at least statistically competent) audience.

FiveThirtyEight doubtless is one of the biggest clearinghouse of statistical writing. But in lieu of compelling writing, their data journalism (for elections, at least) seems to amount to a cacophony of plots between scattered text. I'm not sure how I feel about their writing, but I don't want to cozy up next to the fireplace with it (unlike, say, The New Yorker's profiles).

Problem: two stories spliced into one. I suppose one problem might be that statistical writing necessitates telling two disjoint stories concurrently: the narrative, and "showing one's work" for the statistics. For this reason, it reminds me of Edward Gibbon who wrote with one style for the main text of his Decline and Fall of the Roman Empire, and another style in his footnotes where he "showed his work" (wrestling with sources, comparing differences, weighing evidence, etc.).

Would this suffice for statistical writing oriented towards the lay audience?

The amount of writing necessary to "show my work" in statistics would make the footnotes rather lengthy and daunting. I doubt it would be an adequate or even proper way to write.

I have been tempted to relegate "showing my work" to R Markdown organized in a Git repository structured in a way mimicking Jekyll's directory layout, and showing the main results in this blog. What does this mean?

The git repo has a /_posts/ subdirectory containing "posts". These are the scratch work corresponding to the posts appearing here, on PoliticalArithmetic, in R markdown.

This would separate the two stories into two texts. I'm uncertain if this solution sidesteps the entire problem, as though answering the problem How to handle statistics in writing? with the unsatisfying retort Don't.

Implicit Problem: What is good writing? This, I think, is harder to answer. But it is worth asking, if one wants to write "good writing". Like art, I don't know what defined good writing, but I know good writing when I see it.

At the same time, it seems undesirable to merely have writing coquetted with statistical jargon and numbers.

In this sense, from a literary or (in the Aristotlean usage) rhetorical perspective, statistics is a new "literary device" that is not being adequately handled as such.

"Good statistical writing" has to handle statistics as a literary device to be deployed in "good writing".

Perhaps the key to good statistical writing is the key to all writing: telling a good story. Statistics is another tool in the literary toolbox means towards that end, a teamplayer rather than a star.