Question

Suppose X is a random variable with p(X = 0) = 4/5, p(X = 1) =...

Suppose X is a random variable with p(X = 0) = 4/5, p(X = 1) = 1/10, p(X = 9) = 1/10. Then

(a) Compute Var [X] and E [X].

(b) What is the upper bound on the probability that X is at least 20 obained by applying Markov’s inequality?

(c) What is the upper bound on the probability that X is at least 20 obained by applying Chebychev’s inequality?

Homework Answers

Answer #1
x P(x) xP(x) x2P(x)
0    4/5 0.000 0.000
1    1/10 0.100 0.100
9    1/10 0.900 8.100
total 1.000 8.200
E(x) =μ= ΣxP(x) = 1.0000
E(x2) = Σx2P(x) = 8.2000
Var(x)=σ2 = E(x2)-(E(x))2= 7.200

a)

Var(X)=7.200

E(X)=1.00

b)

upper bound on the probability that X is at least 20 obained by applying Markov’s inequality

P(X>a) <=E(X)/a

P(X>20)<=1/20

c)

upper bound on the probability that X is at least 20 obained by applying Chebychev’s inequality

=P(X>20)=P(X-1>19)>=Var(X)/k2

P(X>20)<=7.2/19

P(X>20)<=36/95

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
Suppose that X is an exponential random variable with pdf f(x) = e^(-x),0<x<∞, and zero otherwise....
Suppose that X is an exponential random variable with pdf f(x) = e^(-x),0<x<∞, and zero otherwise. a. compute the exact probability that X takes on a value more than two standard deviations away from its mean. b. use chebychev's inequality to find a bound on this probability
Suppose X is a discrete random variable with probability mass function given by p (1) =...
Suppose X is a discrete random variable with probability mass function given by p (1) = P (X = 1) = 0.2 p (2) = P (X = 2) = 0.1 p (3) = P (X = 3) = 0.4 p (4) = P (X = 4) = 0.3 a. Find E(X^2) . b. Find Var (X). c. Find E (cos (piX)). d. Find E ((-1)^X) e. Find Var ((-1)^X)
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)
For a continuous random variable X , you are given that the mean is E(X)= m...
For a continuous random variable X , you are given that the mean is E(X)= m and the variance is var(x)= v. Let m=(R+L)/2 Given L = 6, R = 113 and V = 563, use Chebyshev's inequality to compute a lower bound for the following probability P(L<X<R) Lower bound means that you need to find a value  such thatP(L<X<R)>p using Chebyshev's inequality.
Suppose X is a normal random variable with mean μ = 5 and P(X > 9)...
Suppose X is a normal random variable with mean μ = 5 and P(X > 9) = 0.2005. (i) Find approximately (using the Z-table) what is Var(X). (ii) Find the value c such that P(X > c) = 0.1.
Suppose that the random variable X has the following cumulative probability distribution X: 0 1. 2....
Suppose that the random variable X has the following cumulative probability distribution X: 0 1. 2. 3. 4 F(X): 0.1 0.29. 0.49. 0.8. 1.0 Part 1:  Find P open parentheses 1 less or equal than x less or equal than 2 close parentheses Part 2: Determine the density function f(x). Part 3: Find E(X). Part 4: Find Var(X). Part 5: Suppose Y = 2X - 3,  for all of X, determine E(Y) and Var(Y)
Let X be a gamma random variable with parameters alpha = 4 and beta = 4....
Let X be a gamma random variable with parameters alpha = 4 and beta = 4. Using Markov's inequality, calculate an upper bound for the probability that X is greater than or equal to 10.
a) Suppose that X is a uniform continuous random variable where 0 < x < 5....
a) Suppose that X is a uniform continuous random variable where 0 < x < 5. Find the pdf f(x) and use it to find P(2 < x < 3.5). b) Suppose that Y has an exponential distribution with mean 20. Find the pdf f(y) and use it to compute P(18 < Y < 23). c) Let X be a beta random variable a = 2 and b = 3. Find P(0.25 < X < 0.50)
1. Suppose a random variable X has a probability density function f(x)= {cx^2 -1<x<1, {0 otherwise...
1. Suppose a random variable X has a probability density function f(x)= {cx^2 -1<x<1, {0 otherwise where c > 0. (a) Determine c. (b) Find the cdf F (). (c) Compute P (-0.5 < X < 0.75). (d) Compute P (|X| > 0.25). (e) Compute P (X > 0.75 | X > 0). (f) Compute P (|X| > 0.75| |X| > 0.5).
Suppose that X is a binomial random variable with n=5 and p=1/4. Let ? = (?...
Suppose that X is a binomial random variable with n=5 and p=1/4. Let ? = (? − 3) 2 . 1. What is the space of Y? 2. What is the mean of Y? 3. What is the probability that Y<2? (Round to 4 decimal places.) 4. What is the probability that Y=1? (Round to 4 decimal places.)