Practise a pymetrics-style Lengths game: a face flashes, you call its mouth short or long, and some answers win $0.20. See your bias and accuracy.
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Lengths is pymetrics’ version of the probabilistic reward task, a research task about how rewards shape decisions. pymetrics’ patent describes it as a reward learning task: a cartoon face appears with a short or a long mouth, the two lengths differ only slightly, and you press the right arrow for long or the left arrow for short. Correct answers are paid on an uneven schedule, so one length (researchers call it the rich one) pays more often than the other (the lean one). Prep sites add that a rewarded answer shows a small amount of money and that nothing ever tells you whether you were right.
Two things come out of the game. Response bias, usually written log b, measures how far you start answering with the rich length, especially on faces you were unsure about. Discriminability, log d, measures how well you told the two lengths apart regardless of that lean. A lean toward the rich length is the normal pattern, so the game reads more like a measure of how rewards shape your choices than a test with a pass mark. pymetrics does not publish how it scores Lengths: its games feed a model that compares your play with people who do well in the job.
Candidate Falcon’s practice uses the published research timings (a 0.1-second mouth) and its 3:1 reward ratio, with our own simple face and 90 faces in three blocks. Your results reveal which length paid more, then show your accuracy, your response bias and your discriminability, overall and block by block, in plain words.
It is a version of the probabilistic reward task. pymetrics’ patent describes cartoon faces with a short or a long mouth: you press the left arrow for short and the right arrow for long, and correct answers are paid on an uneven schedule, so one length pays more often.
Only some correct answers are rewarded, and one mouth length is rewarded more often than the other. Prep sites say other answers show nothing, so you never see whether an answer was right. That is by design: the game looks at how rewards pull your choices.
They are the two signal-detection measures used with this task. Response bias (log b) shows how far you lean toward answering with the length that pays more. Discriminability (log d) shows how well you tell the two lengths apart. Candidate Falcon’s results explain both in plain words.
pymetrics does not publish a count. Prep sites report 60 or 90. The published research task uses 300 trials in three blocks. Candidate Falcon’s practice uses 90 faces in three blocks of 30.
No. It is independent practice by Candidate Falcon, built from the task in pymetrics’ public patent, the published research and prep-site descriptions, with an original face and screens. It is not affiliated with pymetrics or Harver.
Independent practice by Candidate Falcon, based on pymetrics’ public patents and research and on prep-site descriptions. Not affiliated with pymetrics or Harver, and not their scoring. The game, its art and its wording are original, and practice results are not pymetrics scores. For all 12 games, timing, results and retakes, read the free pymetrics test guide.