Let X1, . . . , Xn ~(iid) Bernoulli(p), and let
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(a) Give an exact expression for .
b) Evaluate your expression from part (a) for n = 200 and p = 4/9.
Let X1, . . . , Xn ~(iid) Bernoulli(p), and let . (a) Give an exact...
Problem 5 Let Xi, X2, ..., Xn be a random sample from Bernoulli(p), 0 < p < 1, and 7.i. Prove that the sample proportion is an unbiased estimator of p, i.e. p,- is an unbiased estimator of p 7.ii. Derive an expression for the variance of p,n 7.iii. Prove that the sample proportion is a consistent estimator of p. 7.iv. Prove that pn(1- Pn)
5. Let Xi, , X, (n 3) be iid Bernoulli random variables with parameter θ with 0<θ<1. Let T = Σ_iXi and 0 otherwiase. (a) Derive Eo[6(X,, X.)]. (b) Derive Ee16(X, . . . , Xn)IT = t], for t = 0, i, . . . , n.
EXERCISE 1. Suppose Xi's are iid Negative Binomial(3,1/4) (a) Compute P(X1 < 5); (b) approximate P(21.9 X; < 1300) (c) descrive the event whose probability is computed in Part (6).
7. Let X1,... , Xn be iid based on f(x; 6) -22e-z?/e where x > 0. Show that θ=-yx? is efficient
6.4.3. Let X1, X2, ..., Xn be iid, each with the distribution having pdf f(x; 01, 02) = (1/02)e-(2–01)/02, 01 < x <ao, -20 < 02 < 0o, zero elsewhere. Find the maximum likelihood estimators of 01 and 02.
1. Suppose that X, X, X, are iid Berwulli(p),0 <p<1. Let U. - x Show that, U, can be approximated by the N (np, np(1-P) distribution, for large n and fixed <p<1. 2. Suppose that X1, X3, X. are iid N ( 0°). Where and a both assumed to be unknown. Let @ -( a). Find jointly sufficient statistics for .
Exercise 6.14 Let y be distributed Bernoulli P(y = 1) unknown 0<p<1 p and P(y = 0) = 1-p f or Some (a) Show that p E( (b) Write down the natural moment estimator p of . (c) Find var (p) (d) Find the asymptotic distribution of vn (-p) as no. as n> OO.
3. Let X1, X2, ..., Xbe iid having the common pdf S 2/r if l<r< , f(1) = 0 elswhere. Is there a real number a such that X a as n o ?
5. Let X1, X2,. , Xn be a random sample from a distribution with pdf of f(x) (0+1)x,0< x<1 a. What is the moment estimator for 0 using the method of moments technique? b. What is the MLE for 0?
1. Let X1, ..., Xn be random sample from a distribution with mean y and variance o2 < 0. Prove that E[S] So, where S denotes sample standard deviation. 10 points