Are these two sub-sigma-algebras independent?

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SUMMARY

The discussion centers on the independence of two sub-sigma-algebras, A and B, derived from partitions F and U of the sample space Ω = {HH, HT, TH, TT}. The partitions are defined as F = {G, K} with G = {HH, TT} and K = Ω \ G, and U = {V, W} where V = {HH, TH} and W = Ω \ V. The conclusion reached is that A and B are not generally independent, as knowing that event G occurred provides information that updates the probability of event V.

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Homework Statement



Let [tex]\Omega=\{HH,HT,TH,TT\}[/tex] and let [tex]F[/tex] and [tex]U[/tex] be two partitions of [tex]\Omega: F=\{G,K\}[/tex] with [tex]G=\{HH,TT\}[/tex] and [tex]K= \Omega\backslash G[/tex], while [tex]U=\{V,W\}[/tex] where [tex]V=\{HH,TH\}[/tex] and [tex]W= \Omega\backslash V[/tex].

If [tex]2^\Omega[/tex] is the [tex]\sigma[/tex]-algebra of [tex]\Omega[/tex], and [tex]A=2^F[/tex] and [tex]B=2^U[/tex] are the sub-[tex]\sigma[/tex]-algebras of [tex]F[/tex] and [tex]U[/tex] (respectively), are [tex]A[/tex] and [tex]B[/tex] independent?


2. The attempt at a solution

[tex]A[/tex] and [tex]B[/tex] are independent if, for any [tex]a \in A[/tex] and [tex]b \in B[/tex], [tex]\Pr(a \cap b) = \Pr(a) \Pr(b)[/tex].

So let's say [tex]a=G[/tex] and [tex]b=V[/tex]. Then [tex]\Pr(G \cap V) = \Pr(HH)[/tex]. Now if the two [tex]\sigma[/tex]-algebras are independent, [tex]\Pr(G)\Pr(V) = \Pr(HH)[/tex].

Since [tex]\Pr(G) = \Pr(HH) + \Pr(TT)[/tex] and [tex]\Pr(V) = \Pr(HH) + \Pr(TH)[/tex] we need to show [tex](\Pr(HH) + \Pr(TT))(\Pr(HH) + \Pr(TH))=\Pr(HH)[/tex].

Now, permit me for not writing out all my algebra, but I'm just not seeing it...
I want to say A and B must be independent because, e.g., if you know G happened (either 2 H's or 2 T's), you still don't know anything about the probability of V or W (an H second, or a T second). Is this right, or am I thinking about it all wrong? I am still trying to get a grasp on this whole sigma-algebra concept, so please go easy on me.
 
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Ok, so me thinks they are not in general independent. If we know G happened, we do indeed have information to update our probability of V (or W).

E.g., if the probabilities over [tex]\Omega=\{HH,HT,TH,TT\}[/tex] are given by the 4-vector [tex](q,r,s,1-q-r-s)[/tex], then
[tex]\Pr(G \cap V) = \Pr(HH) = q[/tex],
[tex]\Pr(G) = \Pr(HH) + \Pr(TT) = 1-r-s[/tex] and
[tex]\Pr(V) = \Pr(HH) + \Pr(TH) = q+s[/tex],
so [tex]\Pr(G)\Pr(V) = \Pr(G \cap V)[/tex] only in the special case [tex](1-r-s)(q+s)=q[/tex] or [tex]q=r(1-r-s)/(r+s)[/tex].

(Right?)
 

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