TOPIC:Finding the mean,variance and kurtosis using the Double expectation formula.
2. Let R be a continuous random variable with the following conditional distribution Rlo~N(0, o2) where...
Let X be a random variable following a continuous uniform distribution from 0 to 10. Find the conditional probability P(X >3 X < 5.5). Chebyshev's theorem states that the probability that a random variable X has a value at most 3 standard deviations away from the mean is at least 8/9. Given that the probability distribution of X is normally distributed with mean ji and variance o”, find the exact value of P(u – 30 < X < u +30).
Let X be a continuous random variable with cumulative distribution function F(x) = 1 − X−α x ≥ 1 where α > 0. Find the mean, variance and the rth moment of X. Question 1: Let X be a continuous random variable with cumulative distribution function where a >0. Find the mean, variance and the rth moment of X
1. (15 points) Let X be a continuous random variable with probability density function f (x) c(1-), 0 < 1, where c is a constant. i) Find the constant c ii) What is the distribution function of X? ii) Let Y 1x<0.5 Find the conditional expectation E(X|Y). 1. (15 points) Let X be a continuous random variable with probability density function f (x) c(1-), 0
3. (10 points) Let X be continuous random variable with probability density function: fx(x) = 7x2 for 1<<2 Compute the expectation and variance of X 4. (10 points) Let X be a discrete random variable uniformly distributed on the integers 1.... , n and Y on the integers 1,...,m. Where 0 < n S m are integers. Assume X and Y are independent. Compute the probability X-Y. Compute E[x-Y.
Let R be a random variable with an exponential distribution with parameter α = 1. Conditional on R, Y has pdf fy|R (y|r) = { ry 0<=y<= sqrt(r/2); otherwise 0 Determine the conditional pdf of R given Y .
4. Suppose that N is a random variable having a conditional Poisson distribution with ability mass function prob- 1 (log 3) PN(i) i 1,2,3,... 2 i (a) Show that the mean of N is 3 log 3 1.6479, 2 and the variance of N is 3(log 3)2 3 log 3 0.7427. 2 4 (b) Calculate the probability P(N -4I 20). (c) Use the Bienaymé-Chebyshev inequality to give a lower bound for the probability that N takes values within 2 standard...
1. Find Fx in terms of φ (t). Is X a continuous random variable ? 2. Compute p(X 0) 3. Compute E(X). Hint: use the CDF expectation formula, and integration by parts. You may assume that lim, t"o(-t) 0 for all n 2 0. 4. Find the CDF Fx (u) 5. Compute V(X). Hint: use Fxa, and follow the same hint of part (3) 1. Find Fx in terms of φ (t). Is X a continuous random variable ? 2....
5. Let X be a discrete random variable. The following table shows its possible values r and the associated probabilities P(X -f(x) 013 (a) Verify that f(x) is a probability mass function (b) Calculate P(X < 1), P(X < 1), and P(X < 0.5 or X > 2). (c) Find the cumulative distribution function of X ompute the mean and the variance of
2. Assume the random variable y has the continuous uniform distribution defined on the interval a to b, that is, f(y) = 1/6 - a), a sy<b. For this problem let a = 0 and b = 2. (a) Find P(Y < 1). (Hint: Use a picture.) (b) Find u and o2 for the distribution.
using excel answer the problem below Let X be a discrete random variable having following probability distribution. x 2 4 6 8 P(x) 0.2 0.35 0.3 0.15 Complete the following table and compute mean and variance for X x P(x) x· P(x) x2. P(x) 2 0.2 4 0.35 6 0.3 8 0.15 Total 1 Expected value E(X) = u = Variance Var = o2 =