I need answer within 20 minutes please please with my best wishes = 0.08 + 0.28 +0.04 = 0.4Example 4-10: A joint discrete probability function f(x.y) is expressed below. FindP(z +yS1). t2-Ifor a = 0, 1, 2; y = 0,1,2; and 0SI+yS2f(1, y) =elsewhereSolution: First we construct the table for the joint discrete probability distribution.f(z, y)29/283/143/283/2813/142.1/280.Then:How find Table in theslotion ?!

Answered: Image /qna-images/answer/2fe78229-9c48-45a6-96d2-da79f3a9edb0.jpg

Example 4-10: A joint discrete probability function f(r, y) is expressed below. Find P(z+yS1). KL 3. for z = 0,1,2; y= 0,1,2; and 0SI+yS2 f(1. y) = elsewhere Solution: First we construct the table for the joint discrete probability distribution. f(2, y) 0. 3/28 9/28 3/28 1 3/14 3/14 2. 1/28 Then: How find Table in the slotion ?!

Example 4-10: A joint discrete probability function f(r, y) is expressed below. Find P(z+yS1). KL 3. for z = 0,1,2; y= 0,1,2; and 0SI+yS2 f(1. y) = elsewhere Solution: First we construct the table for the joint discrete probability distribution. f(2, y) 0. 3/28 9/28 3/28 1 3/14 3/14 2. 1/28 Then: How find Table in the slotion ?!

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...

See similar textbooks

Similar questions

LetX1,X2,...,Xn be a sequence of independent and identically distributed random variables having the Exponential(λ) distribution,λ >0, fXi(x) ={λe−λx, x >0 0, otherwise Define the random variable Y=X1+X2+···+Xn. Find E(Y),Var(Y)and the moment generating function ofY.
(a) Let Y1 , Y2 , · · · , Yn be independent and identically distributed random variables. Show if Y1 < Y2 is independent of the event Y1 < Y3.(b) Let Y1 , Y2 , · · · , Y∞ be dependent random variables with following probability density function; Yn+1 =3Yn with probability 1/3Yn+1 =Yn/3 with probability 2/3 for n ∈ [0, ∞) where Y0 = 1. Compute E[Y1] and E[Y2].
1) Let X1, X2, ..., Xn be a sample of n units from a population with a probability density function f (x I θ)=θxθ-1 , 0<x<1, θ>0 . According to this: Find the estimator of moments for the parameter θ.
LetX1,X2,...,Xn be a sequence of independent and identically distributed random variables having the Exponential(λ) distribution,λ >0, fXi(x) ={λe−λx, x >0 0, otherwise (a) Show that the moment generating function mX(s) :=E(esX) =λ/(λ−s) for s< λ;
A stochastic process (SP) X(t) is given byX(t) = Asin(ωt + Φ)where A and Φ are independent random variables and Φ is uniformly distributed between 0 and 2π.a) Calculate mean E[X(t)]. b) Calculate the auto-correlation RX (t1,t2).c) Is X(t) wide sense stationary (WSS)? Justify your answer.Now consider that X(t) is a Gaussian SP with mean μX (t) = 0.5 and auto-correlation RX (t1,t2) =10e−14 |t1−t2|. Let Z = X(5) and W = X(9) be the two random variables.d) Calculate var(Z), var(W), and var(Z + W). e) Calculate cov(ZW).
Let X1, X2, ..., Xn be a sequence of independent and identically distributedrandom variables having the Exponential(λ) distribution, λ > 0,fXi(x) = λe−λx , x > 00 , otherwise(a) Show that the moment generating function mX(s) := E(e^sX) = λ/λ−s for s < λ;(b) Using (a) find the expected value E(Xi) and the variance Var(Xi).(c) Define the random variable Y = X1 + X2 +· · ·+ Xn. Find E(Y ), Var(Y ) and the moment generating function of Y .(d) Consider a random variable X having Gamma(α, λ) distribution,fX(x) = (λαxα-1/Γ(α)) e−λx , x > 00 , otherwiseShow that the moment generating function of the random variable X is mX(s) =λα 1/(λ−s)α for s < λ, where Γ(α) isΓ(α) = (integral from 0 to inifity ) xα−1e−xdx.(e) What is the probability distribution of Y given in (c)? Explain youranswer.
2)Let X1, X2, ..., Xn be a sample of n units from a population with a probability density function f (x I θ)=θxθ-1 , 0<x<1, θ>0 . According to this: Find the maximum likelihood estimator (MLE) of parameter θ.
X is an exponential random variable with λ =1 and Y is a uniform random variable defined on (0, 2). If X and Y are independent, find the PDF of Z = X-Y2
Consider a random process which is given by Y(t) = t - Z where Z is a random variable with mean 1.2 and second moment 2.5. The autocovariance of the random process X(t) is
Use the moment generating function technique to solve. Let X1, . . . , Xn be independent random variables, such that Xi ∼ Exponential(θ), for i =1, . . . , n. Find the distribution of Y = X1 + · · · + Xn.
Find E(R) and V (R) for a random variable R whose moment-generating function ismR(t) = e2t(1-3t2)-1
b) Let Y1, Y2, ..., Yn be a random sample from a population with probability density function in part a). Show that the best test for the hypothesis in part a) rejects Ho if |yi <c i=1 where c solves the probability equation a = P(II1Yis c[0 = 2). c) Let X1,X2, ..., Xn be a random sample from GAMMA(2,ß) distribution, and consider Y = E-,Xi- Show whether or not Y is a pivotal quantity and give its distribution.