1. If $ is a sample space, discuss U(A) where U is a set functions.
2. show that probability as a measure is finitely additive.
3. proof that lim sup Xn = -lim inf(-Xn)
4. let (V,W) be a measurable space and let P1,P2, .... be a sequence of probability measures defined on W. consider the function defined on W by
P(E) = sum (1/z)Pn(E), for n= 1,2,...... show that P(E) is a probability measure