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OK, let's imagine he we will re-run the study with optimistic assumptions and the result would be that Uber drivers are compensated lavishly (and if we take mor
by nopriorarrests 9y ago
OK, let's imagine he we will re-run the study with optimistic assumptions and the result would be that Uber drivers are compensated lavishly (and if we take more moderate assumptions, they are making adequate money).
And with another set of assumptions result was that they are serverly underpaid.
So, exactly what we have learned here, other then different assumptions yield different results?
- Eridrus 9y agoWe learn that the outcome we care about is highly sensitive to the initial assumptions and we should get data on those assumptions.
- 1337biz 9y agoWe learn that there are no absolutes when using quantitative methods to measure human actions.
- twic 9y agoNothing. But learning that different assumptions yield different results is useful in its own right. It tells you that this study is not capable of answering the question it set out to answer, and you will need to do a better study. Perhaps you have come across interval arithmetic: https://en.wikipedia.org/wiki/Interval_arithmetic https://en.wikipedia.org/wiki/Interval_arithmetic
- deleted 9y ago[deleted]
- dekhn 9y agonot much, which is a big part of the problem.
- pdpi 9y agoIf the re-run concludes that even more optimistic assumptions still lead to underpaid drivers, though, that’s useful information. The key aspect here is the study’s author is willing to change his study based on criticism, to try and determine whether it still produces the same conclusions. That is precisely what science is about!