Consider the geometric random variable X with probability mass function P(X =x)=(1 p)x 1p, x=1,2,3,....
For t <- l o g ( 1 - p ) , c o m p u t e E [ e t X ] .

Consider the geometric random variable X with probability mass function P(X =x)=(1 p)x 1p, x=1,2,3,.... For...
Consider a discrete random variable X with the probability mass function p X ( x ) = x/C , x = 3, 4, 5, 6, 7, zero elsewhere. consider Y = g( X ) = 100/(x^2+1) . b) Find the probability distribution of Y.
Find the probability generating function of a discrete random variable with probability mass function given by pX(k) = qk−1p, k = 1,2,..., where p and q are probabilities such that p + q = 1. We shall see later that this is called the geometric distribution function.
The following mass function describes the distribution for a random variable x: p(x)=0. x={1,2,3,...} (the upper bound of x is ) a) What is the probability x=5? b) What is the probability x ≥ 2? c) What is the probability x=1.5
6. If X1, ..., X, are iid Geometric(p) random variables, derive the probability mass function of the random variable Y, where Y =>
4.8. Let Z be a random variable with the geometric probability mass function where 0 < π < 1. (a) Show that Z has a constant failure rate in the sense that PriZ kZk1 T for k 0, 1,.... (b) Suppose Z' is a discrete random variable whose possible values are 0, 1, and for which Pr(Z'=KZ2k} = 1-π for k 0,1,.... Show that the probability mass function for Z' is p(k).
5. Suppose X is a discrete random variable that has a geometric distribution with p= 1. a. Compute P(X > 6). [5] b. Use Markov's Inequality to estimate P(X> 6). [5] c. Use Chebyshev's Inequality to estimate P(X>6). [5] t> 0 6. Let be the probability density function of the continuous 0 t< 0 random variable X. a. Verify that g(t) is indeed a probability density function. [8] b. Find the median of X, i.e. the number m such that...
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...
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...
1. Suppose that N = {1,2,3} and let X be a random variable such that P(X = 1), P(X = 2) and P(X = 3) are all 1/3. So the probability mass function for X is p(1) = P(2) = P(3) = 1/3. Then, for each n e N= {1,2,...}, we have 3 E[X"] - Ý k"p(k) 1" + 2 + 3" 3 (1) k=1 Calculate E[X], E[X2] and var(X).
3. A random variable X has the probability mass function P(x = k) = (a > 0, k =0,1,2...). (1 + a)! Find E[X], Var(X), and the Moment generating function My(t) = E[ex]