Where p denote the population mean of the original random variable 5.7 Problems . Assume X is a n...
1. Consider a random experiment that has as an outcome the number x. Let the associated random variable be X, with true (population) and unknown probability density function fx(x), mean ux, and variance σχ2. Assume that n 2 independent, repeated trials of the random experiment are performed, resulting in the 2-sample of numerical outcomes x] and x2. Let estimate f x of true mean ux be μΧ-(X1 + x2)/2. Then the random variable associated with estimate Axis estimator Ax- (XI...
Consider a random experiment that has as an outcome the number x. Let the associated variable be X, with true (population) and unknown probability density function fx(x), mean ux. and variance σχ2. Assume that n-2 independent, repeated trials of the random experiment are performed, resulting in the 2-sample of numerical outcomes xi and x2 Let estimate μ X of true mean #xbe μχ = (x1+x2)/2. Then the random variable associated with estimate μ xis estimator random 1. a. Show the...
Please give detailed steps. Thank you. 5. Let {X1, X2,..., Xn) denote a random sample of size N from a population d escribed by a random variable X. Let's denote the population mean of X by E(X) - u and its variance by Consider the following four estimators of the population mean μ : 3 (this is an example of an average using only part of the sample the last 3 observations) (this is an example of a weighted average)...
Let X be a random variable with probability density function (pdf) given by fx(r0)o elsewhere where θ 0 is an unknown parameter. (a) Find the cumulative distribution function (cdf) for the random variable Y = θ and identify the distribution. Let X1,X2, . . . , Xn be a random sample of size n 〉 2 from fx (x10). (b) Find the maximum likelihood estimator, Ỗmle, for θ (c.) Find the Uniform Minimum Variance Unbiased Estimator (UMVUE), Bumvue, for 0...
8. Let X1,...,Xn denote a random sample of size n from an exponential distribution with density function given by, 1 -x/0 -e fx(x) MSE(1). Hint: What is the (a) Show that distribution of Y/1)? nY1 is an unbiased estimator for 0 and find (b) Show that 02 = Yn is an unbiased estimator for 0 and find MSE(O2). (c) Find the efficiency of 01 relative to 02. Which estimate is "better" (i.e. more efficient)? 8. Let X1,...,Xn denote a random...
Let X,,X.X be a random sample of size n from a random variable with mean and variance given by (μ, σ2) a Show that the sample meanX is a consistent estimator of mean 1(X-X)2 converges in probability Show that the sample variance of ơ2-02- b. 1n to Ơ2 . Clearly state any theorems or results you may have used in this proof. Let X,,X.X be a random sample of size n from a random variable with mean and variance given...
Question 10 14 pts Suppose X is a random variable with mean 100 and standard deviation 15. Suppose that we select random samples of size n=81 to construct a sampling distribution of means. Then which of the following is NOT true? Given enough samples, the shape of the sampling distribution will be approximately normal The standard deviation of the sampling distribution is 15/9 The mean of the sampling distribution is 100 The mean of any random sample will be 100...
Question 3 [25] , Yn denote a random sample of size n from a Let Y, Y2, population with an exponential distribution whose density is given by y > 0 if o, otherwise -E70 cumulative distribution function f(y) L ..,Y} denotes the smallest order statistics, show that Y1) = min{Y1, =nYa) 3.1 show that = nY1) is an unbiased estimator for 0. /12/ /13/ 3.2 find the mean square error for MSE(e). 2 f-llays Iat-k)-at 1-P Question 4[25] 4.1 Distinguish...
4. Let X be a random variable that describes the annual counts of tropical cyclones in the North Atlantic. Assume that X1,..., X, is a random sample that describes the counts of tropical cyclones in the North Atlantic during n years and assume they are distributed according to a geometric distribution with probability parameter 8 and p.f. given by fxjex | ) = (1 - 0)*-11{1,2,...,x), 0<O<1. (a) Write the statistical model. (b) Find the maximum likelihood estimator of 0....
Random variable X corresponds to the daily number of accidents in a small town during the first week of January. From the previous experience (prior infor- mation), local police Chief Smith tends to believe that the mean daily number of accidents is 2 and the variance is also 2. We also observe for the current year the sample number of accidents for 5 days in a row: 5,2,1,3,3. Let us assume that X has Poisson distribution with parameter θ ....