4 ms·
A correlation of .09 tells you absolutely nothing. The effect is visible and valid only for between 1 and 4 people out of 100.
by serjester 4y ago
A correlation of .09 tells you absolutely nothing. The effect is visible and valid only for between 1 and 4 people out of 100.
- RugnirViking 4y agoThat's a bit of an unusual way of characterizing it. Isn't a low correlation just implying that there are other factors that have a stronger influence? Which makes sense, I mean personality and lifestyle surely have to have large impacts
- serjester 4y agoA low correlation tells you that the relationship between the two specific variables isn’t meaningful. It doesn’t tell you anything about other variables, maybe you’re thinking of R^2? Regardless both metrics assume you’re dealing with a linear model which is a big assumption in its own right.
- rafaelero 4y agoIf that's the bar you want to use, then you will discover it is also hard to find anything that matters to happiness. As the authors put it: "The correlation between average happiness and log(income) is 0.09 in the experience sampling data, for example, and the difference between the medians of happiness at household incomes of $15,000 and $250,000 is about five points on a 100-point scale. The flattening and accelerating patterns are even smaller modulations of a small effect. However, the emotional effects of other circumstances are also small. KD reported that the effect of an approximately fourfold difference in income is about equal to the effect of being a caregiver, twice as large as the effect of being married, about equal to the effect of a weekend, and less than a third as large as the effect of a headache."