a)
first success at kth trial means there is failure in first (k-1)th trial and success on kth trial
hence
second success on kth trial means there is one success in first (k-1) trials and 2nd success on kth trial
hence
b)
Yes, X follow geometric distribution with probability =p
Y follow negative binomial distribution (Pascal distribution) with r = 2
5. A series of independent Bernoulli(p) trials is performed, labeled 1,2,3,...Let X be the location (label)...
Wiout feplacement. 6.9 Consider a sequence of Bernoulli trials with success probability p. Let X denote the number of trials up to and including the first success and let Y denote the number of trials up to and including the second success. a) Identify the (marginal) PMF of X c) Determine the joint PMF of X and Y. d) Use Proposition 6.2 on page 263 and the result of part (c) to obtain the marginal PMFS of X and Y....
Basic Probability Let us consider a sequence of Bernoulli trials with probability of success p. Such a sequence is observed until the first success occurs. We denote by X the random variable (r.v.), which gives the trial number on which the first success occurs. This way, the probability mass function (pmf) is given by Px(x) = (1 – p)?-?p which means that will be x 1 failures before the occurrence of the first success at the x-th trial. The r.v....
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...
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).
3. Let (X, Y) be a bivariate random variable with joint pmf given by x= 1,2,3, y = 0,1,2,3, ... ,00 f(x, y) 12 0 e.w. (a) Show that f(x, y) is a valid joint pmf. (b) Find fa(x) (i.e. the marginal pmf of X). (c) Find fy(y) (i.e. the marginal pmf of Y). (d) Find P [Y X]
2. Suppose 4 Bernoulli trials, each with success probability p, are con ducted such that the outcomes of the 4 experiments pendent. Let the random variable X be the total number of successes over the 4 Bernoulli trials are mutually inde- (a) Write down the sample space for the experiment consisting of 4 Bernoulli trials (the sample space is all possible sequences of length 4 of successes and failures you may use the symbols S and F). (b) Give the...
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...
5. Develop an acceptance-rejection technique for generating a geometric random variable, X, with parameter p on the range {0,1,2, ...} . (Hint: X can be thought of as the number of trials before the first success occurs in a sequence of independent Bernoulli trials.)
The geometric distribution is a probability distribution of the number X of Bernoulli trials needed to get one success. For example, how many attempts does a basketball player need to get a goal. Given the probability of success in a single trial is p, the probability that the xth trial is the first success is: Pr(x = x|p) = (1 - p*-'p for x=1,2,3,.... Suppose, you observe n basketball players trying to score and record the number of attempts required...
Problem 4 Let X and y be independent Poisson(A) and Poisson(A2) random variables, respectively. i. Write an expression for the PMF of Z -X + Y. i.e.. pz[n] for all possible n. ii. Write an expression for the conditional PMF of X given that Z-n, i.e.. pxjz[kn for all possible k. Which random variable has the same PMF, i.e., is this PMF that of a Bernoulli, binomial, Poisson, geometric, or uniform random variable (which assumes all possible values with equal...