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1. sarche+(OP)[view] [source] 2025-07-10 19:04:01
That depends on the size of the effect you’re trying to measure. If cursor provides a 5x, 10x, or 100x productivity boost as many people are claiming, you’d expect to see that in a sample size of 16 unless there’s something seriously wrong with your sample selection.

If you are looking for a 0.1% increase in productivity, then 16 is too small.

replies(2): >>biophy+F6 >>AvAn12+of
2. biophy+F6[view] [source] 2025-07-10 19:52:33
>>sarche+(OP)
Well it depends on the variance of the random variable itself. You're right that with big, obvious effects, a larger n is less "necessary". I could see individuals having very different "productivities", especially when the idea is flattened down to completion time.
replies(1): >>sarche+bn2
3. AvAn12+of[view] [source] 2025-07-10 20:39:29
>>sarche+(OP)
“A quarter of the participants saw increased performance, 3/4 saw reduced performance.” So I think any conclusions drawn on these 16 people doesn’t signify much one way or the other. Cool paper but how is this anything other than a null finding?
replies(1): >>triple+jc1
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4. triple+jc1[view] [source] [discussion] 2025-07-11 06:33:21
>>AvAn12+of
They show a 95% CI excluding zero in Figure 1. By the usual standards of social science, that's not a null finding. They give their methodology in Appendix D.

For intuition on why it's insufficient to consider N alone, I assume e.g. that you'd greatly increase your belief that a coin was unfair long before 16 consecutive heads--as already noted, the size of the effect also matters. That relationship isn't intuitive in general, and attempts to replace the math with feelings tend to fail.

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5. sarche+bn2[view] [source] [discussion] 2025-07-11 15:45:23
>>biophy+F6
Individuals do have very different productivities, but they are measuring the productivity difference across a single individual.
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