Question

1. Let ?1, . . . ?5 be 5 independent random variables, ?(?? = 1) =...

1. Let ?1, . . . ?5 be 5 independent random variables, ?(?? = 1) = ?(?? = 0) = 1/2. Calculate the variance of the sample variance ?5 = 1 4 ∑︀ ? (??−?[?? ])2 .

Math   Statistics-And-Probability   
0 0
Add a commentTranscribed image text
Next >

Homework Answers

Answer #1

NOTE:: I HOPE YOUR HAPPY WITH MY ANSWER.....***PLEASE SUPPORT ME WITH YOUR RATING......THANK YOU....

0 0
Know the answer?
Your Answer:

Post as a guest

Your Name:

What's your source?

Earn Coins

Coins can be redeemed for fabulous gifts.

Log In

Sign Up

Not the answer you're looking for?
Ask your own homework help question
Similar Questions
Let ? and ? be independent random variables. Random variable ? has mean ?? and variance...
Let ? and ? be independent random variables. Random variable ? has mean ?? and variance ?^2?, and random variable ? has mean ?? and variance ?^2? a) Prove that ?[?⋅?]=??⋅?? Guidance: Start with ?[?⋅?]=ΣΣ??⋅???(?,?)??, and then use the definition of independent random variables. b) Use a) to prove that ???(??+??)=?^2???(?)+?^2???(?). Guidance: Use the formula proved in the class ???(?)=?[?^2]−?^2[?]. c) Let ? =5?+3?. Find the mean and variance of ? in terms of the means and variances of ?...
1) Let the random variables ? be the sum of independent Poisson distributed random variables, i.e.,...
1) Let the random variables ? be the sum of independent Poisson distributed random variables, i.e., ? = ∑ ? (top) ?=1(bottom) ?? , where ?? is Poisson distributed with mean ?? . (a) Find the moment generating function of ?? . (b) Derive the moment generating function of ?. (c) Hence, find the probability mass function of ?. 2)The moment generating function of the random variable X is given by ??(?) = exp{7(?^(?)) − 7} and that of ?...
1. Let ?1 and ?2 be two independent random variables with normal distribution with expectation 0...
1. Let ?1 and ?2 be two independent random variables with normal distribution with expectation 0 and variance 1. (1) Find the covariance between ?1 + ?2 and ?1 − ?2. (2) Find the probability that ?2 1 + ?2 2 ≤ 2. (3) Find the expectation of ?2 1 + ?2^2 . 2. Estimate the approximated value of (︂ 10000 5100 )︂ = 10000! 5100!4900! by central limit theorem.
Let ? and ? be two independent random variables with uniform distribution. ?(? = 0|? =...
Let ? and ? be two independent random variables with uniform distribution. ?(? = 0|? = ?, ? = ?) = 1 − ?, ?(? = 1|? = ?, ? = ?) = ?(1 − ?) and ?(? = 2|? = ?, ? = ?) = ??. 1.Write down the conditional expectation ?[?|? = ?] and ?[?|? = ?] as functions of ?.
Let ? and ? be two independent random variables with uniform distribution. ?(? = 0|? =...
Let ? and ? be two independent random variables with uniform distribution. ?(? = 0|? = ?, ? = ?) = 1 − ?, ?(? = 1|? = ?, ? = ?) = ?(1 − ?) and ?(? = 2|? = ?, ? = ?) = ??. 1. Find the conditional joint p.d.f. (the posterior) ??,?|?=?. 2.Write down the conditional expectation ?[?|? = ?] and ?[?|? = ?] as functions of ?.
Let {?1,?2, … , ?? } be ? independent random draws from any given distribution with...
Let {?1,?2, … , ?? } be ? independent random draws from any given distribution with finite expected value ? and variance ? 2 > 0. Let ?̅ = 1 ? ∑ ?? ? ?=1 denote the average draw, which in turn is a random variable with its own distribution. This question works through successive proofs to derive the expected value and variance of this distribution, culminating in a proof of the Law of Large Numbers. a. Show that ?(??...
5. Let X1, X2, . . . be independent random variables all with mean E(Xi) =...
5. Let X1, X2, . . . be independent random variables all with mean E(Xi) = 7 and variance Var(Xi) = 9. Set Yn = X1 + X2 + · · · + Xn n (n = 1, 2, 3, . . .) (a) Find E(Y2) and E(Y5). (b) Find Cov(Y2, Y5). (c) Find E (Y2 | X1). (d) How should your answers from parts (a)–(c) be modified if the numbers “2”, “5”, “7” and “9” are replaced by m,...
Let U and V be two independent standard normal random variables, and let X = |U|...
Let U and V be two independent standard normal random variables, and let X = |U| and Y = |V|. Let R = Y/X and D = Y-X. (1) Find the joint density of (X,R) and that of (X,D). (2) Find the conditional density of X given R and of X given D. (3) Find the expectation of X given R and of X given D. (4) Find, in particular, the expectation of X given R = 1 and of...
Let X and Y be independent and identically distributed random variables with mean μ and variance...
Let X and Y be independent and identically distributed random variables with mean μ and variance σ2. Find the following: a) E[(X + 2)2] b) Var(3X + 4) c) E[(X - Y)2] d) Cov{(X + Y), (X - Y)}
Let X and Y be independent and normally distributed random variables with waiting values E (X)...
Let X and Y be independent and normally distributed random variables with waiting values E (X) = 3, E (Y) = 4 and variances V (X) = 2 and V (Y) = 3. a) Determine the expected value and variance for 2X-Y Waiting value µ = Variance σ2 = σ 2 = b) Determine the expected value and variance for ln (1 + X 2) c) Determine the expected value and variance for X / Y
ADVERTISEMENT
Need Online Homework Help?

Get Answers For Free
Most questions answered within 1 hours.

Ask a Question
ADVERTISEMENT