2. Let X be a Bernoulli random variable with probability of X -1 being a. a)...
7. Let X1,....Xn random sample from a Bernoulli distribution with parameter p. A random variable X with Bernoulli distribution has a probability mass function (pmf) of with E(X) = p and Var(X) = p(1-p). (a) Find the method of moments (MOM) estimator of p. (b) Find a sufficient statistic for p. (Hint: Be careful when you write the joint pmf. Don't forget to sum the whole power of each term, that is, for the second term you will have (1...
The Bernoulli random variable takes values 0 and 1, and has probability function f(x) = px (1 − p)1−x(a) By calculating f(0) and f(1), give a practical example of a Bernoulli experiment, and a Bernoulli random variable. (b) Calculate the mean and variance of the Bernoulli random variable.
Let X be a random variable with cumulative distribution function(a) Find the probability density function fX(x), (b) Find the moment generating function MX(s) for s < 3, (c) Find the mean and variance of X.
Advanced Statistics, I need help with (c) and (d) 2. Let X1, X2, ..., Xn be a random sample from a Bernoulli(6) distribution with prob- ability function Note that, for a random variable X with a Bernoulli(8) distribution, E [X] var [X] = θ(1-0) θ and (a) Obtain the log-likelihood function, L(0), and hence show that the maximum likelihood estimator of θ is 7l i= I (b) Show that dE (0) (c) Calculate the expected information T(e) EI()] (d) Show...
7 Let X be a Bernoulli random variable with P(X = 1) = 4. Consider a sample from X of size n. Formulate both the LLN and the CLT. Remember that you must calculate the mean and the variance of X to answer this question
1. [26 pts Let Uı, , Un be independent, identically distributed Unifomn random variables with (continu- ous) support on (0, b), where b> 0 is a parameter. (a) Define the random variable Y :--Σί 1 log(U,), where log is the natural logarithm function. De- termine the probability density function (pdf) p(y; b) ofY by explicitly computing it (b) Based on the pdf you found in part (a) above, determine the third moment of Y, i.e., EY] (c) Suppose now that...
Let X variable Y by be a normal random variable with mean 0 and variance 1. We define the random y2 if x 20, Y= (a For t E R, compute Mr()-Elen'], the moment generating function of Y. Compute EY
9. The random variable x is distributed normally with mean Mx. and variance 6 and random Variable Y is normally distributed with mean & and Variance or 2x=34 is distributed hormally with mean 12 and variance 42 Assume Independence Find values Ux and by. Possible answers: Mx = 18 & Gyr by=va mx-128 6y=842 My 686y=2 ty=-68
I. The random variables X,, where P(success) = P(X = 1) = p = 1-P(X = 0) for1,2,..., represent a series of independent Bernoulli trials. Let the random variable Y be the trial number on which the first success is achieved (a) Explain why the probability mass function of Y is f(y) = pqy-1, y = 12. where q 1- p. State the distribution of Y. 2 part of your answer you should verify this is a marimum likelihood estima-...
Let X be a random variable with the following probability density function: 0 otherwise. Using following relationship ueudu a. Show that fy (y) is a valid probability density function b. Show that the moment generating function My (t) =-for t 2 (2-t) c. Obtain the first and second raw moments. d. Using these raw moments determine the mean and variance Let X be a random variable with the following probability density function: 0 otherwise. Using following relationship ueudu a. Show...