The weak law of large numbers the probability that the

Info iconThis preview shows page 1. Sign up to view the full content.

View Full Document Right Arrow Icon
This is the end of the preview. Sign up to access the rest of the document.

Unformatted text preview: E{Y} = E{g(X)} = sum p(x)g(x) Or integral f(x)g(x)dx •  •  •  •  X a random variable, Y a random variable, Z etc Then X + Y + Z + etc is also What is the expecta4on of the sum? The sum of the expecta4ons! The variance •  X a random variable •  With expecta4on µ •  Then the variance is the expecta4on of (X- µ)2 •  What is the variance...
View Full Document

This document was uploaded on 03/02/2014 for the course STATS 4150 at Barnard College.

Ask a homework question - tutors are online