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Hi thickhead:
fantastic answer. many thanks.
I still have no idea about (e),how to estimate P(0.8<X+Y<0.801)?
suppose random variables X and Y has joint pdf f(x,y)=k-y 0<y<x^2<1
a) find k
b) find marginal pdf f(x) and the conditional pdf f(x|1/2) and cdf F(y|1/2);
c) find P(X<Y|Y>1/2), E(X|1/2) and E(X|Y>1/2)
d) what's the correlation between X and Y?
e) find the value of pdf of U=X+Y evaluated at u=0.8 and estimate P(0.8<X+Y<0.801)
Any help here would be greatly appreciated!
Hi bobbym:
do you have any idea about (d)? which method will not involve any differentiation to find mean and variance?
thanks anyway
you are right, i make a mistake here . I have no idea about the second part question
'express the first and second derivative of r(0) in terms of E(W) and Var(W)'
Hi:
sorry about that ,I don't know why there are some box appeared in your browser.
you can ignore these box ,the question is find the first and second derivative of r(t) and express the first and second derivative of r(0) in terms of E(W) and Var(W)
Hi bobbym:
I'm also confused about (b) ,but I don't think there are missing characters. shall we consider about this :
r(t) = logm(t) , r'(t)=m'(t)/m(t) r''(t)=[m''(t) m(t)+(m'(t))^2] / (m(t))^2
and then we find r'(0)=m'(0) / m(0) =EW/m(0) .does this idea correct ? but how to use the EW and VarW to eliminate m(0)? thank you for your reply
Suppose a rv Y has mgf m(t)=e^[k(e^t -1)] / (1-bt)^a
a) obtain the mean and variance of Y (differentiate this mgt twice)
b)Suppose m(t) is the mgf of a rv W. Let r(t) be the natural logarithm of m(t),
i.e. r(t) = logm(t). Find r'(t) and r''(t) , and express r'(0) and r''(0)in terms of EW and VarW.
c) Use the result in (b) to find the mean and variance of the rv Y in (a)
d)Find the mean and variance of the rv Y in (a) using a method which does not involve any differentiation.
really difficult for me
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