Letfo(X) = {(1/7)0X₁, X₂,..., Xn be i.i.d. samples with pdf0 < X < 0,0 > 0,Otherwise.Assume:1 Estimator 1 is Ô = 2 X.2 Estimator 2 is Ô = X(n).Answer the following questions:Q1 Are these estimators unbiased?Q2 Are these estimators consistent?

Answered: Image /qna-images/answer/18cd0158-b974-4105-bd8d-dd8fbb325439.jpg

Answered: Let X₁, X₂,..., Xn be i.i.d. samples…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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1:10 O b A O "Q. * a E (19 For numbers 1 to 3: The thermal condition in a cave is critical for sustaining a bat population. A sudden change in the temperature is related to deaths of bats in hundreds. An attempt to measure the degree of association between the temperature (in °C) and death toll (number of deaths) was done using 20 caves with reported cases of massive death among bats. Assume that temperature and death toll are bivariate normal. Given below is the R software output: > cor.test(temp , death) Pearson's product-moment correlation data: temp and death t - -1.4403, df - 148, p-value - 0.1519 alternative hypothesis: true correlation is not equal to e 95 percent confidence interval: -0.27269325 0.04351158 sample estimates: cor -0.1175698
Book Pages (x) Price (y) A 500 $7.10 B 700 7.60 C 750 9.10 D 590 6.60 E 560 7.60 F 650 7.10 G 475 5.10 (a) Develop a least squares estimated regression line. (Round your numerical values to three decimal places.) (b) Compute the coefficient of determination. (Round your answer to four decimal places.) Explain its meaning. (Give your answer as a percent. Round your answer to two decimal places.) The value of the coefficient of determination tells us that % of the variability in |--?-- ☑ has been explained by the least squares regression equation.
Hello, could I please get a solution for A through D
B4
A company manufactures products in its factory in Turkey for sale in Asia. Products sold in different countries differ in terms of the power outlet as well as the language of the manuals. Currently, the company assembles and packs products for sale in individual countries. The distribution of weekly demand in different countries is normally distributed with means and standard deviations as shown in the table Assume that demand in countries to be independent. Given that the lead time from the Turkey factory is (X/4) weeks, how much safety inventory does the company require in Asia if it targets a CSL level of 95 percent?X= 96 b. The company builds a distribution center in Asia. It will ship base products to this center. When an order is received, the center will assemble power supplies, add manuals, and ship the products to the appropriate country. The base products are still to be manufactured in Turkey with the same lead time. How much saving of safety inventory can the company expect…
Question 2. Show that, for a simple linear regression, R² = ry, where R² is the coefficient of determination and rxy is the sample correlation between Y and X. Hint: Σ" (Υ - Y)2 Σ1(Y₁-Y)²¹ SxY √SXXSYY' where Sxy = 1 (X; — X)(Y; — Y), Sxx = ₁1(X; - X)², Syy = ₁₁(Y₁ - Y)². R² = "XY =
N= 150 observations were collected on a time series that was identified as a AR(2) time series. The following statistics were computed from the data. Mean - 45.0 Variance 15.6 Autocorrelation function (up to lag 5) r1 = 0.80, r2 = .50, rз = .26, r4 = -.10, rs = 0.08: == Estimate the parameters of the model using the method of moments.
If our data were a perfect fit to our regression model, such that y; = ŷ;, we would expect | to be in the CI on p.
assessment.casa.uh.edu/Assessment/Root/Pages/TestTaker/Quiz.aspx?id=2F507231-0111-4CFC-8C26-F38ED05C3949 f) O None of the above Review Later Question 7 If the LSRL relating the independent variable x and the dependent variable y for a given problem is ŷ = 2x + 4, then an increase of 1 unit in x is associated with an increase of how many units in y? a) 06 b) 00 d) O1 e) 04 Review Late
Suppose you obtain the following regression model, E[y]=91+79*x1 +20*x1*x2. What is the impact of a 39 unit change of x1 on the expected value of y when x2 is at its mean of 40?
Suppose that n= 195 I.I.d. observations for (Y, X;) yleld the following regression results: v= 32.68 + 67.55Xx, SER= 18.63, R = 0.84 (15.7) (12.5) Another researcher is interested in the same regression, but he makes an error when he enters the data into the regression: He enters each observation twice, so he has 390 observations (with observation 1 entered twice, observation 2 entered twice, and so forth). Which of the following eatimated parameters change result? (Check all that apply) O A. The estimated intercept and slope. O B. The R of the regression. Yc. The standard error of the regrussion (SER). YD. The standard errors of the estimated coefficients. Using the 390 observations, what results will be produced by his regression program? Ý= 32.68 + 67.55X, SER =.R = 0.84 (Round your responses to two decimal places)
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Let X₁, X₂,..., Xn be i.i.d. samples with pdf (G) 0 > 0, 0 fe (X) = 0 < X < 0, Otherwise. Assume: 1 Estimator 1 is ê= 2 X. 2 Estimator 2 is Ô = X(n). Answer the following questions: Q1 Are these estimators unbiased? Q2 Are these estimators consistent?