Suppose X, Y, Z are iid observations from a Poisson distribution with parameter λ, which is unknown. Consider the 3 estimators T1 = X + Y − Z, T2 = 2X + Y + Z 4 , T3 = 3X + Y + Z 5 . (a) Which among the above estimators are unbiased? (b) Among the class of unbiased estimators, which has the minimum variance?

Suppose X, Y, Z are iid observations from a Poisson distribution with parameter λ, which is unknown. Consider the 3 estimators T1 = X + Y − Z, T2 = 2X + Y + Z 4 , T3 = 3X + Y + Z 5 . (a) Which among the above estimators are unbiased? (b) Among the class of unbiased estimators, which has the minimum variance?

A First Course in Probability (10th Edition)

10th Edition

ISBN:9780134753119

Author:Sheldon Ross

Publisher:Sheldon Ross

Chapter1: Combinatorial Analysis

Section: Chapter Questions

Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...

See similar textbooks

Similar questions

A study was conducted by a group of neurosurgeons. They compared a dynamic system (Z-plate) and a static system (ALPS plate) in terms of the number of acute postoperative days in the hospital spent by the patients. The descriptive statistics for these data are as follows: for 14 patients with dynamic system, the sample mean number of acute postoperative days was 7.36 with standard deviation of 1.22; for 6 patients with static system the sample mean number of acute postoperative days was 10.5 with sample standard deviation of 4.59. Assume that the numbers of acute postoperative days in both populations are normally distributed. We wish to estimate µ1 − µ2 with a 99 percent confidence interval. Can you assume unknown population variance are equal. a. Degrees of freedom and t-value are b. Margin of error and confidence interval are c. Based on your interval in part (b), we can state with 99 percent confidence that the average numbers of acute postoperative days in two populations i.…
Consider the performance function Y= 2X1-2X2+8X3 are all normally distributed random variables with μΧ1 = 10.4 ; μΧ2 = 11.8 ; μΧ3= 11.5Vx1 = 4 % , Vx2 = 5% ; Vx3 = 8 % X1 X2 X3q = 1 0,8 6 X1 0,8 1 0,5 X2 -----> correlation of Matrix 0,6 0,5 1 X3 Y < 0; failure occurs 15 simulations Pf =? . Determine the probability of failure ? (Reliability of Structures)
You have been asked to determine if two different production processes have different mean numbers of units produced per hour. Process 1 has a mean defined as µ₁ and process 2 has a mean defined as µ2. The null and alternative hypotheses are Ho: μ₁ −μ₂ ≤0 and H₁ : µ₁ −µ₂ > 0. The process variances are unknown but assumed to be equal. Using random samples of 36 observations from process 1 and 49 observations from process 2, the sample means are 60 and 50 for populations 1 and 2 respectively. Complete parts a through d below. Click the icon to view a table of critical values for the Student's t-distribution. a. Can you reject the null hypothesis, using a probability of Type I error α = 0.05, if the sample standard deviation from process 1 is 28 and from process 2 is 23? (Round to three decimal places as needed.) The test statistic is t =
Define the Distributed Lag Model with Additional Lags and AR(p) Errors?
a) & b)
Many properties of the fabric used in different textiles, such as sheets and clothing, are influenced by whether the diameter of yarn used in the creation of the textile is consistent. Therefore, various methods can be used to measure the diameter of yarn at specified intervals, such as every 2mm, to determine the consistency of the diameter. These measurements are normally distributed. Suppose that one textile manufacturer will not use any yarn in which the variance of the diameters is greater than 0.0009mm. In order to ensure that the yarn is usable, the diameter of a length of yarn is measured at 400 random intervals. The variance of those measurements is found to be 0.000992mm. Does this evidence provide support that the batch of yarn is unusable by the manufacturer? Use a 0.005 level of significance. Step 2 of 3 : Compute the value of the test statistic. Round your answer to three decimal places.
Suppose a data set from a bike share company contains the number of daily bike rentals at each of 6 stations for the 23 weekdays of a particular month, i.e. we have Yij for i = 1, ..., 23 and j 1,...6. Write down a hierarchical normal model that can be used to estimate the mean number of bike rentals at each station. You can assume that the unknown variance o? of the number of bike rentals is the same for each station.
We are planning an experiment comparing three fertilizers. We will have six experimental units per fertilizer and will do our test at the 5% level. One of the fertilizers is the standard and the other two are new; the standard fer- tilizer has an average yield of 10, and we would like to be able to detect the situation when the new fertilizers have average yield 11 each. We expect the error variance to be about 4. What sample size would we need if we want power .9?
1) Suppose the following model y; = B1 + u; Where is assumed to be normally distributed with mean zero and variance ơ² . Calculate analytically, following OLS technique, ß, and Var(ß,).
2. In building an arena, steel bars with a mean ultimate tensile strength of 400 Megapascal (MPa) with a variance of 81 MPa were delivered by the manufacturer. The project engineer tested 50 steel bars and found out that the mean ultimate tensile strength is 390 MPa. The decision for the extension of the contract with the manufacturer depends on the engineer. Test the hypothesis whether there is no significant difference between the two means using a two - tailed with a = 0.01.
Let X1, X2, X3, ..., X, be a random sample from a distribution with known variance Var(X,) = o², and unknown mean EX, = 0. Find a (1 – a) confidence interval for 0. Assume that n is large.
3. Let X, X2, .. X5, be a random sample from a population having mean u and variance o?, and let ô, =(x, + X, + X, + X,) and ô, =(2x, + X, + X, - X,) be two estimates of u. * Which of these two estimators is unbiased? * Which is the better estimator, and why? %3D