Question

Let X be a random variable such that P(X=k) = k/10, for k = 1,2,3,4. Let...

Let X be a random variable such that P(X=k) = k/10, for k = 1,2,3,4. Let Y be a random variable with the same distribution as X. Suppose X and Y are independent. Find P(X+Y = k), for k = 2,...,8.

Homework Answers

Answer #1

The Joint PMF of X and Y is given by: , x,y=1,2,3,4

{Since X and Y are independent}

which are the required probabilities.

Know the answer?
Your Answer:

Post as a guest

Your Name:

What's your source?

Earn Coins

Coins can be redeemed for fabulous gifts.

Not the answer you're looking for?
Ask your own homework help question
Similar Questions
2. Let X be a continuous random variable with pdf given by f(x) = k 6x...
2. Let X be a continuous random variable with pdf given by f(x) = k 6x − x 2 − 8 2 ≤ x ≤ 4; 0 otherwise. (a) Find k. (b) Find P(2.4 < X < 3.1). (c) Determine the cumulative distribution function. (d) Find the expected value of X. (e) Find the variance of X
let x be a discrete random variable with positive integer outputs. show that P(x=k) = P(...
let x be a discrete random variable with positive integer outputs. show that P(x=k) = P( x> k-1)- P( X>k) for any positive integer k. assume that for all k>=1 we have P(x>k)=q^k. use (a) to show that x is a geometric random variable.
Let X be a discrete random variable with probability mass function (pmf) P (X = k)...
Let X be a discrete random variable with probability mass function (pmf) P (X = k) = C *ln(k) for k = e; e^2 ; e^3 ; e^4 , and C > 0 is a constant. (a) Find C. (b) Find E(ln X). (c) Find Var(ln X).
(a) It is given that a random variable X such that P(X =−1) =P(X = 1)...
(a) It is given that a random variable X such that P(X =−1) =P(X = 1) = 1/4, P(X = 0) = 1/2. Find the mgf of X, mX(t) (b) Let X1 and X2 be two iid random varibles such that P(Xi =1)=P(Xi =−1)=1/2, i=1,2. Use the mgfs to prove that X and Y =(X1+X2)/2 have the same distribution
Let X denote a random variable that follows a binomial distribution with parameters n=5, p=0.3, and...
Let X denote a random variable that follows a binomial distribution with parameters n=5, p=0.3, and Y denote a random variable that has a Poisson distribution with parameter λ = 6. Additionally, assume that X and Y are independent random variables. Derive the joint probability distribution function for X and Y. Make sure to explain your steps.
Let X be a normally distributed random variable with mean 5. 1. If P(4 ≤ X...
Let X be a normally distributed random variable with mean 5. 1. If P(4 ≤ X ≤ 4.6) = .240, find P(5.4 ≤ X ≤ 6). 2. Suppose P(X ≤ k) = .5 for some number k. What is the value of k? 3. Suppose P(X ≤ ℓ.) = .841, for some mystery value ℓ.. Approximately how many standard deviations above or below the mean is the value ℓ.?
Let X~Poisson(4) random variable and Y an independent Bin(10,1/2) random variable. (a) Use Markov's inequality to...
Let X~Poisson(4) random variable and Y an independent Bin(10,1/2) random variable. (a) Use Markov's inequality to find an upper bound for P(X+Y > 15). (b) Use Chebyshev's inequality to find an upper bound for P(X+Y > 15)
Let X be a Poisson random variable with parameter λ and Y an independent Bernoulli random...
Let X be a Poisson random variable with parameter λ and Y an independent Bernoulli random variable with parameter p. Find the probability mass function of X + Y .
1. Let X be a discrete random variable with the probability mass function P(x) = kx2...
1. Let X be a discrete random variable with the probability mass function P(x) = kx2 for x = 2, 3, 4, 6. (a) Find the appropriate value of k. (b) Find P(3), F(3), P(4.2), and F(4.2). (c) Sketch the graphs of the pmf P(x) and of the cdf F(x). (d) Find the mean µ and the variance σ 2 of X. [Note: For a random variable, by definition its mean is the same as its expectation, µ = E(X).]
Let X denote a random variable that follows a binomial distribution with parameters n=5, p=0.3, and...
Let X denote a random variable that follows a binomial distribution with parameters n=5, p=0.3, and Y denote a random variable that has a Poisson distribution with parameter λ = 6. Additionally, assume that X and Y are independent random variables. Using the joint pdf function of X and Y, set up the summation /integration (whichever is relevant) that gives the expected value for X, and COMPUTE its value.
ADVERTISEMENT
Need Online Homework Help?

Get Answers For Free
Most questions answered within 1 hours.

Ask a Question
ADVERTISEMENT