Posted on Thu 20 June 2024 in TDDA • Tagged with TDDA, reproducibility, errors, interpretation
I was at the tenth PyData London Conference last weekend, which was excellent, as always. One of the keynote speakers was Rebecca Bilbro who gave a rather brilliant (and cleverly titled) talk called Mistakes Were Made: Data Science 10 Years In.
The title is, of course, a reference to the …
Continue readingPosted on Sun 08 January 2023 in TDDA • Tagged with stats, bias, interpretation
On Episode 258 of Marco Arment and “Underscore” David Smith’s podcast Under the Radar, and then on Episode 516 of Marco & co’s Accidental Tech Podcast, Marco describes the fact that his data suggests that about 12% of his users don’t have logged-in iCloud accounts with iCloud Drive …
Continue readingPosted on Wed 06 January 2016 in TDDA • Tagged with tdda, errors, interpretation
Guest Post by Patrick Surry, Chief Data Scientist, Hopper
Every year, Expedia and ARC collaborate to publish some annual statistics about domestic airfare, including their treatment of the perennial question "How far in advance should you book your flight?" Here's what they presented in their report last year:
Although there …
Continue readingPosted on Fri 13 November 2015 in TDDA • Tagged with tdda, implementation, interpretation, correctness
"Why is this lying bastard lying to me?"
Louis Heren,1 often attributed to Jeremy Paxman.
In a previous post, we made a distinction between two kinds of errors—implementation errors and errors of interpretation. I want to amplify that today, focusing specifically on interpretation.
The most important question to …
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