Problem 3. Recall that if X follows a poisson distribution with parameter λ, the probability mass functionof X is given by:px (x) =e-11xx!X = = {0, 1, 2, ...}(a) If px (2) = 2px (0), calculate px(3).(b) Use this poisson random variable X to approximate P(Y = 4), where Y is a binomial random variablewith n = 2000 and p = x/n.

A binomial distribution can be approximated by a Poisson distribution under the following…

Answered: Problem 3. Recall that if X follows a…

A First Course in Probability (10th Edition)

10th Edition

ISBN:9780134753119

Author:Sheldon Ross

Publisher:Sheldon Ross

Chapter1: Combinatorial Analysis

Section: Chapter Questions

Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...

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J 1 Problem 126. Let X and Y be discrete random variables with joint probability mass function pX,Y (x, y) = C/[(x + y − 1)(x + y)(x + y + 1)], x, y = 1, 2, 3, . . . Determine the marginal mass functions of X and Y
Problem 1. A continuous random variable X is defined by f(x)=(3+x)^2/16 -3 ≤ x ≤ -1 =(6-2x^2)/16 -1 ≤ x ≤ 1 =(3-x^2)/16 -1 ≤ x ≤ 3 a)Verify that f(x) is density. b)Find the Mean
Problem#1: On the desk of an office of a Banking Company, the arrivals of the customers follow poisson law and an average at every 10 minutes a customer arrives. The officer responsible takes on an average 6 minutes to serve a customer, assuming the exponentially distributed. Find out the average arrival rates for(a) 1 hour(b) 15 minutes(c) 8 hours
Problem 1. Consider the following density function. f(x )=[ (kx) ^ (2/3) * 0 < x < 2 Find the value of k. Find the cumulative distribution function ( CDF) of X Find the inverse of the CDF. Simulate a random sample of 10000 values from the above distribution by using inversetransformation and find the mean and the variance of those values, and write the Rcode.
Find the cumulative distribution function of the random variable X representing the number of defectives in Problem #5. Then using F(x), find (a) P(X = 1); (b) P(0 < X ≤ 2).
Question 3 A product is classified according to the number of defects it contains and the factory that produces it. Let X and Y be the random variables that represent the number of defects per unit (taking on possible values of 0, 1, 2, or 3) and the factory number (taking on possible values 1 or 2), respectively. The entries in the table represent the joint possibility mass function of a randomly chosen product.
Question 1: Let X and Y denote two discrete random variables taking the values in x and y respectively. The collected data over time is represented in the following stochastic model: ?(? = ?, ? = ?) = ?(?, ?). a) Check that this table describes a valid joint probability mass function. b) Find the marginal probabilities of ?? (3)??? ??(2). c) Find following the probability: (i) ?(? = 2, ? = 2), (ii) ?(? = 2 | ? = 2) , (iii) ?(? ≤ 3) d) Find the mean of X. e) Are the X and Y independent? Explain. Note: Kindly assess the table in the picture attached for more information.
If Y is a discrete random variable with possible values of 1, 2, and 4, and the probability mass function is given by P(Y = 1) = 0.2, P(Y = 2) = 0.5, and P(Y = 4) = 0.3, what is the variance of Y?
Question 1 : Suppose that the probability density function (p.d.f.) of the life (in weeks) of a certain part is f(x) = 3 x 2 (400)3 , 0 ≤ x < 400. (a) Compute the probability the a certain part will fail in less than 200 weeks. (b) Compute the mean lifetime of a part and the standard deviation of the lifetime of a part. (c) To decrease the probability in part (a), four independent parts are placed in parallel. So all must fail, if the system fails. Let Y = max{X1, X2, X3, X4} denote the lifetime of such a system, where Xi denotes the lifetime of the ith component. Show that fY (y) = 12 y 11 (400)12 , y > 0. Hint : First construct FY (y) = P(Y ≤ y), by noticing that {Y ≤ y} = {X1 ≤ y} ∩ {X2 ≤ y} ∩ {X3 ≤ y} ∩ {X4 ≤ y}. (d) Determine P(Y ≤ 200) and compare it to the answer in part (a)
If the moment generating function of a random variable X is: (1/3+(2/3)e t ) 5 find P (X > 3).
Question 1.2 Consider the function f (x) = (1/24(x^2 +1) 1 < or = x < or = 4) = (0 otherwise) Calculate P (x = 3) Calculate P (2 < or = x < or = 3) Question 1.3 Consider the function f (x) = (k - x/4 1 < or = x < or = 3) = (0 otherwise) which is being used as a probability density function for a continuous random variable x? a. Find the value of K b. Find P (x < or = 2.5)
Question 4 (Part B a-c)A petrol station in the capital Kingstown has a single pump manned by one attendant. Vehicles arrive at the rate of 20 customers per hour and petrol filling takes 2 minutes on an average. Assume the arrival rate is Poisson probability distribution and service rate is exponentially distributed. Arrivals tend to follow a Poisson distribution, and service times tend to be exponential. The attendant is paid $10 per hour, but because of lost goodwill and sales, station loses about $15 per hour of customer time spent waiting for the attendant to service and order. The Petrol station is considering adding a second pump with an attendant to service customers. The station would pay that person the same $10 per hour. What is the probability that no customers are in the system (Po)?b. What is the average number of customers waiting for service (Lq)?c. What is the average number of customers in the system (L)? SHOW ALL WORKINGS

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