Timeline for X-Y correlation when there are multiple values of Y for every value of X

5 events

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Feb 21, 2017 at 10:39	history	edited	z8080	CC BY-SA 3.0	added 61 characters in body
Feb 19, 2017 at 4:26	comment	added	Glen_b		ctd.,,. between $E(Y\|X)$ and $X$ to be well-described by a linear relationship. However, for a $Y$ variable consisting of counts other ways of describing the relationship are more common (specifically, GLMs are often used, which, depending on the nature of the count variable will look at various possible curvilinear relationships (specifically where a transformed $E(Y\|X)$ is seen as linear in $X$
Feb 19, 2017 at 4:25	comment	added	Glen_b		The "one value of Y for every value of X" problem is a common problem in regression-type applications. However, since there's clearly variation in $Y$ at any given value of $X$, it's not $Y$ itself that is seen as being in a functional relationship to $X$ but some aspect of the conditional distribution of $Y$, such as its conditional mean so $E(Y\|X)$ can have a functional relationship with $X$, for example. I don't think that's in any way different for your problem. There's nothing really wrong with a Pearson correlation for discrete data if you expect the relationship ...ctd
Feb 17, 2017 at 20:55	answer	added	rolando2		timeline score: 1
Feb 17, 2017 at 19:38	history	asked	z8080	CC BY-SA 3.0