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Oct
20
comment Normal Distribution, The “Y” Value
I see, so the "Y" is unbounded. As the variances becomes infinitly small the "Y" becomes infinitly large. But is there any interpretation to th "Y". P(X=c)=Some Y Value. I know the area underneath this single point is 0, but does the "Y" value tell us something? Ok forget that the distribtuion is continious, and we have possible X values as our X-Scale, and the frequency as our Y-scale. Should I divide the frequency of the event by the number of observation to get the probability of the event?
Oct
20
comment Normal Distribution, The “Y” Value
But as a pdf shouldn't it be the case the function is always less than 1? I mean the area underneath the function should sum to 1 but if the pdf is a probability function shouldn't that probability be less than or equal to 1?