Problem 0.2 Recall the Geometric(p) distribution where X-number of flips of a coin until you get...
Recall the Geometric(p) distribution where X = number of flips of a coin until you get a head (H) with Pr(H) = p. The distribution is Pr(X = x) = (1 − p) (x−1) p for x = 1, 2, . . . , with mean E(X) = ∑ x=1∞ (x(1 − p) (x−1) p) = 1/p, which can be obtained by brute force. An easier way to find the mean is to condition on the first toss, say Y...
Problem 0.1 Let X be the number of people who enter a bank by time t>0. Suppose ke-t k! for k 0,1,2,., and for t>s > 0, and k-r=0,1,2, . . . . (a) Find Pr(X2 = k | X,-1) for k = 0, 1, 2, . . . . (b) Find E[X2 X1-1 Useful information: Don't eat yellow snow, and et-L=0 tk/k! Problem 0.2 Recall the Geometric(p) distribution where Xnumber of flips of a coin until you get a...
Problem o.1 Let X, be the number of people who enter a bank by time t > 0. Suppose k! for k- 0,1,2,..., and s (t - s)k-e-t for t>s> 0, and k2r 0,1,2,.... (a) Find Pr[X2 k| X 1 for k 0,1,2,.... (b) Find E2 X1 1 Useful information: Don't eat yellow snow, andeot/k! Problem o.2 Recall the Geometric(p) distribution where X- number of flips of a coin until you get a head (H) with Pr(H) - p. The...
You flip a coin 100 times. Let X= the number of heads in 100 flips. Assume we don’t know the probability, p, the coin lands on heads (we don’t know its a fair coin). So, let Y be distributed uniformly on the interval [0,1]. Assume the value of Y = the probability that the coin lands on heads. So, we are given Y is uniformly distributed on [0,1] and X given Y=p is binomially distributed on (100,p). Find E(X) and...
Suppose we toss a coin (with P(H) p and P(T) 1-p-q) infinitely many times. Let Yi be the waiting time for the first head so (i-n)- (the first head occurs on the n-th toss) and Xn be the number of heads after n-tosses so (X·= k)-(there are k heads after n tosses of the coin). (a) Compute the P(Y> n) (b) Prove using the formula P(AnB) P(B) (c) What is the physical meaning of the formula you just proved? Suppose...
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...
A discrete random variable X follows the geometric distribution with parameter p, written X ∼ Geom(p), if its distribution function is A discrete random variable X follows the geometric distribution with parameter p, written X Geom(p), if its distribution function is 1x(z) = p(1-P)"-1, ze(1, 2, 3, ). The Geometric distribution is used to model the number of flips needed before a coin with probability p of showing Heads actually shows Heads. a) Show that fx(x) is indeed a probability...
Need help with this Problem 4 A discrete random variable X follows the geometric distribution with parameter p, written X ~Geom(p), if its distribution function is fx(x) = p(1-p)"-1, xe(1, 2, 3, . . .} The Geometric distribution is used to model the number of flips needed before a coin with probability p of showing Heads actually shows Heads. a) Show that Ix(z) is indeed a probability inass function, i.e., the sum over all possible values of z is one...
A coin with probability p is tossed until the first head occurs. It is then tossed again until the first tail occurs. Let X be the total number of tosses required. 1) Find the distribution function of X. 2) Find the mean and variance of X.
We have seen that the geometric distribution Geo(p) is used to model a random variable, X that records the trial number at which the first success isachieved after consecutive failures in each of the preceding trials ("success" and failure being used in a very loose sense here). Here, p is the success probability in each trial. We described the geometric distribution using the probability mass function: f(X)(1- p)*-1p, which computes the probability of achieving success in the xth trial after...