Hi, folks. This is my first foray into posting on this forum, so apologies if there is a protocol I am unaware of.
Let's say I have a binomial data set - m number of data points with a vaule of 0 and m number of data points with a value of 1. I have one data point (z) with the value of 0.5 (see below).
y x
y x
y x
y z x
----------------------------------------
0 0.5 1
We want to recognize data point z as a "maximally abnormal" (i.e. the maximum outlier possible with the given distribution) data point b/c it is furthest outside of both clusters.
How do we do this? In general, how do we take a data point and, without assuming a normal distribution, compute how "different" it is from the given distribution?
Thanks in advance.
Let's say I have a binomial data set - m number of data points with a vaule of 0 and m number of data points with a value of 1. I have one data point (z) with the value of 0.5 (see below).
y x
y x
y x
y z x
----------------------------------------
0 0.5 1
We want to recognize data point z as a "maximally abnormal" (i.e. the maximum outlier possible with the given distribution) data point b/c it is furthest outside of both clusters.
How do we do this? In general, how do we take a data point and, without assuming a normal distribution, compute how "different" it is from the given distribution?
Thanks in advance.