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The article does make that assertion, and it is as an illustration: > The result was a series of visualizations that map the wide gamut of potential effects re
by scott_s 8y ago
The article does make that assertion, and it is as an illustration:
> The result was a series of visualizations that map the wide gamut of potential effects researchers could detect in the three repositories, and they reveal several important things: One, that small changes in analytical approach can lead to dramatically different findings along that spectrum. Two, that the correlation between technology use and well-being is negative. And three, that this correlation is very, very small, explaining—at most—0.4 percent of the variation in adolescent well-being.
> To put it in perspective, the researchers compared the link between technology use and adolescent well-being to that of other factors examined by the large-scale data sets. "Using technology is about as associated with well-being as eating potatoes," Przybylski says. In other words: hardly at all. By the same logic, bullying had an effect size four times greater than screen use. Smoking cigarettes? 18 times. Conversely, getting enough sleep and eating breakfast were positively associated with adolescent well-being at a magnitude 44 and 30 times that of technology use, respectively.
- kbutler 8y agoX is about Y. X is hardly different from 0. X is at most 0.4 How close is X to 0? How close is Y to 0? (Don't know) Could X be 0? Could Y be 0? Could Y be .001? Could Y be -.001? (Yes)
- scott_s 8y agoThat's a fine interpretation. But the way you phrased your objection, one could think that potatoes was not actually in the data set, and they pulled the comparison out of thin air. But it was in the data set, and it was a real comparison.
- kbutler 8y agoThe article included the quote in such a way that it appears to be pulled out of thin air - I was surprised when I checked other links to find that it was in the data. And that all feels like casting a wide net anomaly hunting, rather than hypothesis testing, but that's probably not relevant at this point.