3. Assume that X is the number of large earthquakes (with magnitude 2 7.5) occurring in...
The discrete probability distribution of X is shown below, where X represents the number of earthquakes in the U.S. that are 7.5 (Richter Scale) or higher in a given year. X= Number of Earthquakes 0 1 P(x) 0.5 0 .4 | 0.1 2 14. Referring to Problem C, the probability that there will be no earthquakes in the U.S.is a) 0.1 b) 0.6 c) 1.0 d) 0.5 15. Referring to Problem C, the probability of at least 2 earthquakes is...
Question 3 [17 marks] The random variable X is distributed exponentially with parameter A i.e. X~ Exp(A), so that its probability density function (pdf) of X is SO e /A fx(x) | 0, (2) (a) Let Y log(X. When A = 1, (i) Show that the pdf of Y is fr(y) = e (u+e-") (ii) Derive the moment generating function of Y, My(t), and give the values of t such that My(t) is well defined. (b) Suppose that Xi, i...
4. Let X1,X2, x 2) distribution, and let sr_ Ση:1 (Xi-X)2 and S2 n-l Σηι (Xi-X)2 be the estimators of σ2. (i) Show that the MSE of S" is smaller than the MSE of S2 (ii) Find ElvS2] and suggest an unbiased estimator of σ. n be a random sample from N (μ, σ
2. Suppose XX2,X is a random sample from an exponential distribution with . Let X(1) minX1,X2, Xn), the minimum of the sample mean (a) Show that the estimator 6nx is an unbiased estimator of 8. (hint: you were asked to derive the distribution of X for a random sample from an exponential distribution on assignment 2 -you may use the result) (b) X, the sample mean, is also an unbiased estimator of . Which of the unbiased estimators, or X,...
Estimator properties: 6 Estimators properties 6.1 Exercise 1 In order to estimate the average number of hours that children spend watching tv, a Bernoulli sample of size n = 5 children was selected from a primary school. Let X be the variable that represents the hours spent watching tv, let E(X)-μ the parameter to estimate and var(X-σ2 the variance. Compare the following two proposed estimators Τι 1. Compare the two estimators for u on the basis of their bias 2....
3. (5 marks) Let U be a random variable which has the continuous uniform distribution on the interval I-1, 1]. Recall that this means the density function fu satisfies for(z-a: a.crwise. 1 u(z), -1ss1, a) Find thc cxpccted valuc and the variancc of U. We now consider estimators for the expected value of U which use a sample of size 2 Let Xi and X2 be independent random variables with the same distribution as U. Let X = (X1 +...
2 Let X1, X2, ...,X, be independent continuous random variables from the following distribution: f(3) = ox-(0-1) where : > 1 and a > 1 You may use the fact: E[X]- .- 2.1 Show that the maximum likelihood estimator of a is ômle = Ei log Xi 2.3 Derive a sufficient statistic for a. What theorem are you using to determine sufficiency? 2.4 Show that the fisher information in the whole sample is: 1(a)= 2.5 What Cramer Rao lower bound...
Assume a population of 2, 4, and 9. Assume that samples of size n 2 are randomly selected with replacement from the population. Listed below are the nine different samples. Complete parts a through d below 4.9 9,9 2,2 2,4 2,9 4,4 9,2 9.4 a. Find the value of the population standard deviation σ (Round to three decimal places as needed.) b. Find the standard deviation of each of the nine samples, then summarize the sampling distribution of the standard...
You are given the following probability density function, φ2(x), for the cosine of the surface angle, X, of a laser etching tool. The distribution function has one parameter, α, and one constant, c. PX (x) =竺2-1 a) What is the value of the constant, c? b) What is the moment estimator for α? c) Explain how you can determine if this moment estimator is unbiased. d) Let S (ai... 2s) denote a random sample of sample size n-24 with sample...
Please let me know how to solve 7.6.5. 6.5. Let Xi, X2,. .. X, be a random sample from a Poisson distribution with parameter θ > 0. (a) Find the MVUE of P(X < 1)-(1 +0)c". Hint: Let u(x)-1, where Y = Σ1Xi. 1, zero elsewhere, and find Elu(Xi)|Y = y, xỉ (b) Express the MVUE as a function of the mle of θ. (c) Determine the asymptotic distribution of the mle of θ (d) Obtain the mle of P(X...