Question

In: Statistics and Probability

Let X1 and X2 be two independent random variables having a chi-squared distribution with degrees of...

Let X1 and X2 be two independent random variables having a chi-squared distribution with degrees of freedom n1 and n2, respectively. Let
Y1 = (X1) / (X1 + X2) and Y2 = X1 + X2
(a) Find the joint p.d.f. of Y1 and Y2
(b) Find the marginal p.d.f. of each of Y1 and Y2
(c) Are Y1 and Y2​​​​​​​​​​​​​​ independent ? Justify your answer.

Solutions

Expert Solution

Joint and marginal distribution and independence.


Related Solutions

Consider independent random variables X1, X2, and X3 such that X1 is a random variable having...
Consider independent random variables X1, X2, and X3 such that X1 is a random variable having mean 1 and variance 1, X2 is a random variable having mean 2 and variance 4, and X3 is a random variable having mean 3 and variance 9. (a) Give the value of the variance of X1 + (1/2)X2 + (1/3)X3 (b) Give the value of the correlation of Y = X1- X2 and Z = X2 + X3.
Let X1, X2, . . . be a sequence of independent and identically distributed random variables...
Let X1, X2, . . . be a sequence of independent and identically distributed random variables where the distribution is given by the so-called zero-truncated Poisson distribution with probability mass function; P(X = x) = λx/ (x!(eλ − 1)), x = 1, 2, 3... Let N ∼ Binomial(n, 1−e^−λ ) be another random variable that is independent of the Xi ’s. 1) Show that Y = X1 +X2 + ... + XN has a Poisson distribution with mean nλ.
Let X1, X2, . . . be iid random variables following a uniform distribution on the...
Let X1, X2, . . . be iid random variables following a uniform distribution on the interval [0, θ]. Show that max(X1, . . . , Xn) → θ in probability as n → ∞
Let X1, X2, X3, X4, X5 be independent continuous random variables having a common cdf F...
Let X1, X2, X3, X4, X5 be independent continuous random variables having a common cdf F and pdf f, and set p=P(X1 <X2 <X3 < X4 < X5). (i) Show that p does not depend on F. Hint: Write I as a five-dimensional integral and make the change of variables ui = F(xi), i = 1,··· ,5. (ii) Evaluate p. (iii) Give an intuitive explanation for your answer to (ii).
2. Let X1, X2, . . . , Xn be independent, uniformly distributed random variables on...
2. Let X1, X2, . . . , Xn be independent, uniformly distributed random variables on the interval [0, θ]. (a) Find the pdf of X(j) , the j th order statistic. (b) Use the result from (a) to find E(X(j)). (c) Use the result from (b) to find E(X(j)−X(j−1)), the mean difference between two successive order statistics. (d) Suppose that n = 10, and X1, . . . , X10 represents the waiting times that the n = 10...
Problem 1 Let X1, X2, . . . , Xn be independent Uniform(0,1) random variables. (...
Problem 1 Let X1, X2, . . . , Xn be independent Uniform(0,1) random variables. ( a) Compute the cdf of Y := min(X1, . . . , Xn). (b) Use (a) to compute the pdf of Y . (c) Find E(Y ).
Let X1 and X2 be independent standard normal variables X1 ∼ N(0, 1) and X2 ∼...
Let X1 and X2 be independent standard normal variables X1 ∼ N(0, 1) and X2 ∼ N(0, 1). 1) Let Y1 = X12 + X12 and Y2 = X12− X22 . Find the joint p.d.f. of Y1 and Y2, and the marginal p.d.f. of Y1. Are Y1 and Y2 independent? 2) Let W = √X1X2/(X12 +X22) . Find the p.d.f. of W.
Let X1 and X2 be independent UNIF(0,1) random variables and consider the transformations Y1= X1X2 and...
Let X1 and X2 be independent UNIF(0,1) random variables and consider the transformations Y1= X1X2 and Y2 =X1/X2. Find the joint pdf of Y1 and Y2 and indicate their joint support of Y1 and Y2. Show Work.
Let X1, X2,..., Xnbe independent and identically distributed exponential random variables with parameter λ . a)...
Let X1, X2,..., Xnbe independent and identically distributed exponential random variables with parameter λ . a) Compute P{max(X1, X2,..., Xn) ≤ x} and find the pdf of Y = max(X1, X2,..., Xn). b) Compute P{min(X1, X2,..., Xn) ≤ x} and find the pdf of Z = min(X1, X2,..., Xn). c) Compute E(Y) and E(Z).
Let X1,X2,… be a sequence of independent random variables, uniformly distributed on [0,1]. Define Nn to...
Let X1,X2,… be a sequence of independent random variables, uniformly distributed on [0,1]. Define Nn to be the smallest k such that X1+X2+⋯+Xn exceeds cn=n2+12n−−√, namely, Nn = min{k≥1:X1+X2+⋯+Xk>ck} Does the limit limn→∞P(Nn>n) exist? If yes, enter its numerical value. If not, enter −999. unanswered Submit You have used 1 of 3 attempts Some problems have options such as save, reset, hints, or show answer. These options follow the Submit button.
ADVERTISEMENT
ADVERTISEMENT
ADVERTISEMENT