LetX be a random variable that takes on values between 0 and c. (i.e P(0 X-c)-1)....
Problem 3. Let X be a discrete random variable that takes values in N. Show that if X is memory-free then it must be the case that X Geo(p) for some p. (Hint a useful first step might be to show that P(X > t)= P(X > 1)' for all t E N.) Problem 3. Let X be a discrete random variable that takes values in N. Show that if X is memory-free then it must be the case that...
3. (8 pt, 2 each) (Ross) Let X be a random variable taking values in the finite interval 0, c]. You may assume that X is discrete, though this is not necessary for this problem (a) Show that EX c and EX2 cEX (b) Use the inequalities above to show that Var(X) <c2[u(1-u)] u=EXE[0, 1]. where (e) Use the result of part (b) to show that Var(cx) se/ (d) Use the result in (c) to bound the variance of a...
Consider a random variable X, that takes values 0 and 1 with probabilities P(0) = P(1) = 0.5. Then, X = 0 with probability 0.5 and X = 1 with probability 0.5. What is the expected value of X? 0 0.25 0.5 1
The random variable X takes only the values 0, ±1, ±2. In addition, it is known that P(-1 <X <2) 0.2 P(X = 0) = 0.05 PCI 1) = 0.35 P(X 2) = P(X = 1 or-1) (a) Find the probability distribution of X (b) Compute E[X]
The Bernoulli random variable takes values 0 and 1, and has probability function f(x) = px (1 − p)1−x(a) By calculating f(0) and f(1), give a practical example of a Bernoulli experiment, and a Bernoulli random variable. (b) Calculate the mean and variance of the Bernoulli random variable.
A discrete random variable A takes values {1, 2, 4} with probabilities specified as follows: P[A = 1] = 0.5, P[A = 2] = 0.3 and P [A = 4] = 0.2 Given A= ), a discrete random variable N is Poisson distributed with rate equal to 1, that is: 9 P[N = n|A = 1] = in n! el Hint If N is Poisson distributed with rate 1, its expectation and variance are as follows: E[N] = Var [N]...
Please show your work with a brief but logical explanation. Suppose X is a random variable with p(X 0) 4/5, p(X-1) 1/10, p(X-9) 1/10. Then (a) Compute Var [X] and B [X] (b) What is the upper bound on the probability that X is at least 20 obained by applying Markov's inequality? c) What is the upper bound on the probability that X is at least 20 obained by applying Chebychev's inequality'? Suppose X is a random variable with p(X...
PART B: Application 5. Suppose that you observe a random variable X. and then, on the basis of the observed value. you attempt to predict the value of a second random variable Y. Let Y denote the predictor or an estimator of Y ; that is, if X is observed to equal , then Y is your prediction for the value of Y, and your goal is to choose Y so that it tends to be close to Y First,...
2. For a discrete random variable X, with CDF F(X), it is possible to show that P(a < X S b)-F(b) - F(a), for a 3 b. This is a useful fact for finding the probabil- ity that a random variable falls within a certain range. In particular, let X be a random variable with pmf p( 2 tor c-1,2 a. Find the CDF of X b. Find P(X X 5). c. Find P(X> 4). 3. Let X be a...
Recall that a Bernoulli random variable with parameter p is a random variable that takes the value 1 with probability p, and the value 0 with probability 1 - p. Let X be a Bernoulli random variable with parameter 0.7. Compute the expectation values of X, denoted by E[X*1, for the following three values of k: k = 1,4, and 3203. E [X] = E [X4 E [X3203