5) Here is the probability that we get even number of successes in trials.
1)This can happen in 2 ways.
i) Odd number of success in first trials followed by a success whose probability is the compound probability,
ii) Even number of success in first trials followed by a failure whose probability is the compound probability,
The above cases being disjoint (probabilities can be added),
The proof is complete.
2) The above equation can be rewritten as
Note that (0 is even and always happens). The sum to above geometric series is
The limit is (note that )
Thus, it is proved that does not depend on .
Problem 6. Consider the n independent trails in Problem 5. Let On be the probability that...
Problem 1 Consider a sequence of n+m independent Bernoulli trials with probability of success p in each trial. Let N be the number of successes in the first n trials and let M be the number of successes in the remaining m trials. (a) Find the joint PMF of N and M, and the marginal PMFs of N and AM (b) Find the PMF for the total number of successes in the n +m trials. Problem 1 Consider a sequence...
You perform a sequence of m+n independent Bernoulli trials with success probability p between (0, 1). Let X denote the number of successes in the first m trials and Y be the number of successes in the last n trials. Find f(x|z) = P(X = x|X + Y = z). Show that this function of x, which will not depend on p, is a pmf in x with integer values in [max(0, z - n), min(z,m)]. Hint: the intersection of...
Exercise 2. Consider n independent trials, each of which is a success with probability p. The random variable X, equal to the total number of successes that occur, is called a binomial random variable with parameters n and p. We can determine its expectation by using the representation j=1 where X, is a random variable defined to equal 1 if trial j is a success and to equal otherwise. Determine ELX
[PLEASE USE HINT] Problem 10: 10 points Suppose that (Xi, X2,... are independent identically distributed binary variables taking (0 1) values with probability PX here 0<q Introduce the new variable, M such that the event {M = k} occurs when three consecutive successes appear at the first time. In other words, event [M = kj, where k-3, occurs if and only if and there is no previous occurrence of three consecutive successes. Use conditioning techniques to derive the expected value,...
N(0, 1) and let S be a 4. Let Z random sign independent of Z, i.e., S is 1 with probability 1/2 and -1 with probability 1/2. Show that SZ N(0,1) 5. Let Z N(0, 1) and X = Z2. This distribution is called chi-square with degree of freedom. Calculate P(1 < X < 4) one N(0, 1) and let S be a 4. Let Z random sign independent of Z, i.e., S is 1 with probability 1/2 and -1...
Problem 5 (10 points). Suppose that the independent Bernoulli trials each with success probability p, are performed independently until the first success occurs, Let Y be the number of trials that are failure. (1) Find the possible values of Y and the probability mass function of Y. (2) Use the relationship between Y and the random variable with a geometric distribution with parameter p to find E(Y) and Var(Y).
Let X be the number of successes that result from 2n independent trials, when each trial is a success with probability p. Show that P[X=n] is a decreasing function of n.
Please answer d,e,f and g, thank you! roblem 1. Let (U common p.d.f. i 1 be a sequence of ii.d. discrete random variables with f(k) for k = 1, 2, 3 and for n 21 let Sn = Σ,u. (a) Find the probability that S2 is even. (b) Find the probability that Sn is even given that S,-1 is even. (e) Find the probability that Sn is even given that S-1 is odd. (d) Let pn P(Sn is even). Find...
Let P be some probability measure on sample space S = [0, 1]. (a) Prove that we must have limn→∞ P((0, 1/n) = 0. (b) Show by example that we might have limn→∞ P ([0, 1/n)) > 0.
Let Mn be the maximum of n independent U(0, 1) random variables. a. Derive the exact expression for P(|Mn − 1| > ε). Hint: see Section 8.4. b. Show that limn→∞ P(|Mn − 1| > ε) = 0. Can this be derived from Chebyshev’s inequality or the law of large numbers?