An exercise on ab-test-checkout

An exercise worth doing on ab-test-checkout.

6,000 rows, 8 columns, one row per exposed user. Six thousand users randomised across a control and two variants, with conversion, revenue, device, and a novelty effect that fades over the first week.

Every dataset here is synthetic, which is a deliberate trade. It costs realism and buys three things: we can ship it CC0 with no licence trap, we can bake in the exact quirk a lesson needs, and nobody's real records end up in a tutorial.

Something to try: Try a t-test on revenue, then a bootstrap, and compare the intervals. The SQL playground has it loaded already, and the data explorer will profile every column in one pass if you would rather look before you query.

select *
from ab_test_checkout
limit 20;

The file is generated from a fixed seed, so the CSV you download today is byte-identical to the one from last year. That matters more than it sounds: it means a lesson can say "row 412 is the interesting one" and still be right in eighteen months.

Download it, break it, keep it. CC0 — no attribution required, no account, no email.