i) Show that the standard score of the sample mean X, is equal to Y. ii) Show that the mean and variance of the random variable Y are 0 and 1, respectively. iii) Show using the moment generating function technique that Y is a standard normal random variable. iv) What is the probability that V2 is between 0.02 and 5022
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- Let Y1, Y2, ... , Yn be a random sample of size n from a gamma distribution with parameters α = 1and β = 2. Derive the probability distribution of the sample mean Y̅ using moment-generatingfunctions.Let X1, X2, …, Xn be a random sample from the Normal distribution N() (a) Using method of moments to estimate the parameters and . (b) Are those estimators unbiased?Let X1, X2,…. Xn be a random sample from Poisson distribution with parameter , obtain Cramer Rao lower bound for the variance of unbiased estimators of lamda
- Suppose that X is a random variable with the density:f(x) = ( θxθ−1 if x ∈ (0, 1) 0 if otherwise The parameter θ > 0 is to be estimated. Suppose that x1 = 0.3, x2 = 0.6 are the sample data. Get the estimate of θ(a) using the Moment Method;(b) using the Maximum Likelihood Method.Let � be a random variabale satisfying �(0,1).Without using the normalcdf(...) function, find �(�≤-2).Consider random variables X1, · · · Xn, independent and identically distributed such that each Xi ∼N (0, 1). Write down an expression for the joint pdf of the n-dimensional random vector (X1, · · · Xn).(i.e. what is the distribution of a random sample of n standard normal random variables
- Suppose that the lifetime, X, and brightness, Y, of a light bulb are modeled as continuous random variables. Let their joint pdf be given by:f(x,y)=λ_1λ_2e^{-λ_1x-λ_2y},x,y>0 •Are lifetime and brightness independent?•Are lifetime and brightness uncorrelated?Let X1, X2, ... Xn random variables be independent random variables with a Poisson distribution whose parameters are l1, l2, ... ln, respectively. Which of the following is the moment generating function of the random variable Z defined as (the little image)?Consider a random sample X1, . . . , Xn of size n ≥ 2 from the normal distribution N (0, σ2 ) with parameter σ2 > 0 Suppose that the prior distribution for σ2 is inverse Gamma with density
- Suppose the random variable y is a function of several independent random variables, say x1,x2,...,xn. On first order approximation, which of the following is TRUE in general?An insurance company supposes that each person has an accident parameter and that the yearly number of accidents of someone whose accident parameter is λ is Poisson distributed with mean λ. They also suppose that the parameter value of a newly insured person can be assumed to be the value of a gamma random variable with parameters s and α. (a) If a newly insured person has n accidents in her first year, find the conditional density of her accident parameter. (b) Also, determine the expected number of accidents that she will have in the following year.Data collected over a number of years show that whena broker called a random sample of eight of her clients,she got a busy signal 6.5, 10.6, 8.1, 4.1, 9.3, 11.5, 7.3, and5.7 percent of the time. Assuming that these figures canbe looked upon as a random sample from a continuous uniform population, use the estimators obtained in Exer-cise 57 to estimate the parameters α and β.