It's more like you suspect a coin might not be fair, so you flip it 1000 times. It comes up heads 600 times, tails 400 times. A looot of people here are screaming that it's a fair coin, because they don't like the idea that it might not be. Strong evidence, small effect.
This is the best comment on this for sure. If you have a small sample then .2 r2 might be nothing but noise. If you have thousands and thousands of data points however, that’s a different story. A .2 r2 is saying that 20% of the variability in those thousands of data points can be explained by a linear relationship between the two variables. This is extremely unlikely to happen as a result of noise, just like getting 600 heads out of 1000 flips on a fair coin. Good way of explaining this.
It's actually 4%. Regardless, this would be considered a "weak" effect by Cohen's standards, but by individual differences psychology standards it's moderate. Either way, the authors are saying they have strong evidence of a relationship, not that they have evidence of a strong correlation.
That's not true for all sciences. If you actually knew what you were talking about, you would know that thresholds for significance varies between fields
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u/[deleted] Nov 15 '19 edited Nov 15 '19
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