Probability Review - Expectations

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Homework Statement




I'm trying to review basic probability; haven't looked at it in a couple of years. Am I on the right track here?

A and B are independent random variables, uniform distribution on [0,1]. Find: E(min(A,B))

2. The attempt at a solution

[tex]\displaystyle\int_{0}^{1}\int_{0}^{a}b\,db\,da + \displaystyle\int_{0}^{1} \int_{a}^{1}a\,db\,da[/tex]

[tex]=\displaystyle\int_{0}^{1}\frac{a^2}{2}\,da+\int_{0}^{1}a-a^2\,da[/tex]

[tex]=1/6+3/6-2/6=1/3[/tex]
 
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Thanks. I also need to find [tex]E(|A-B|)[/tex] and [tex]E((A+B)^2)[/tex]

For the second one: [tex]E((A+B)^2)=E(A)+2E(A)E(B)+E(B)[/tex] and so on ...

Can somebody give me a hint for: [tex]E(|A-B|)[/tex]
 
Last edited:
spitz said:
Thanks. I also need to find [tex]E(|A-B|)[/tex] and [tex]E((A+B)^2)[/tex]

For the second one: [tex]E((A+B)^2)=E(A)+2E(A)E(B)+E(B)[/tex] and so on ...

Can somebody give me a hint for: [tex]E(|A-B|)[/tex]

The claim [tex]E((A+B)^2)=E(A)+2E(A)E(B)+E(B)[/tex] is false. For general bivariate (A,B) the correct result is [tex]E (A+B)^2 = E(A^2) + E(B^2) + 2E(AB).[/tex] If A and B happen to be independent (or, at least, uncorrelated) then we have [itex]E(AB) = E(A) \cdot E(B),[/itex] but for general (A,B) this fails. More generally, if A has variance [itex]\sigma_A^2[/itex], B has variance [itex]\sigma_B^2[/itex] and the pair (A,B) has covariance [itex]\sigma_{AB},[/itex] then
[tex]E(A+B)^2 = \mbox{Var}(A+B) + (EA + EB)^2 = \sigma_A^2 + \sigma_B^2 + 2 \sigma_{AB} + (EA + EB)^2.[/tex]

RGV
 
Oh yes, I forgot to square [itex]A[/itex] and [itex]B[/itex]. For this problem they are independent (guess I should have mentioned that). So:
[tex]E((A+B)^2)=E(A^2)+E(B^2)+2E(A)B(A)[/tex]