2. Consider the negative binomial distribution with parameters r,p and having pmf nb(x;r,p) = Ꮖ (* + r − ¹) p*(1 − p)² p'(1-p) x = 0, 1, 2, 3, … …. (a) Supposer 2, then show that T-1 p = X+r−1 is an unbiased estimator for p. (Hint: write out E(p), then cancel out x+r −1 inside the sum). (b) A reporter wishing to interview five individuals who support a certain candidate (for presidency?) begins asking people whether they support (S) or not support (F) the can- didate. If they observe the following sequence of responses SFFSfffffffffffSSS, esti- mate p the true proportion of people who support the candidate. How does the estimate change if the following sequence of responses were observed ssssfffffffffffffs. Does it matter to the estimate when the first four S's appear in the sequence of responses?
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- Let Y, represent the ith normal population with unknown mean 4, and unknown variance of for i=1,2. Consider independent random samples, Ya, Ya, Yin, of size n,, from the ith population with sample mean Y, and sample variance S?=₁1(Y-₁². (h) Find the standard error of U₂ in part (g), assuming that of = 0² = 0². (i) Discuss how the distribution of Y₁ - Y₂ can be used to test the equality of the two population means, #₁1 and 12, when o=o=o² is known. (i) Define appropriate rejection regions, in terms of Y₁-Y₂, for testing Ho: #₁ = 1₂ against a two-sided alternative hypothesis at the a level of significance.Suppose that f(x) = 0.125x for 0 < x < 4 Determine the mean and the variance of X.10. True or false. (i) –1 < Cov(X, Y) <1 for any two random variables X, Y. (ii) When two random variables have zero correlation they must be independent. (iii) Cov(13.X, 13X) = 13Var(X). Those statements that you mark as false, explain why and give a corrected version.
- 12. Let random variable X has geometric distribution with p.d.f. a a f(x) = pq*", k =1,2,3,... Show that E[X]=- and Var(X)= 4 without using its moment generating function.Suppose X, Y, Z are i.i.d. from a Normal distribution with mean μ and variance 4. You have to compare between three estimators for μ, which are T1:= (2X + Y)/3 , T2:= (X + Y − Z)/2 , T3:= (Y + 2Z)/2 . (a) Which among the above are unbiased estimators for μ? (b) Which among these have the smallest variance? (c) Can you propose an estimator for μ which is better than the 3 above? You have to show that your estimator is indeed better.4. Consider the following joint pdf, where X is the amount of time (in hours) employees at a certain company spend commuting per day and Y is the percentage of each commute spent in a traffic delay. f(x) = }4 0 < x < 4, 05. Find the method of moments estimator of a based on a random sample from a gamma distribution with B=2. XGAM(a,2) www.2. [7+3+5+10] Consider the following model where et is i.i.d and |p| < 1. Yt = Bo+B1xt + ut Ut = put-1 + et, t = 1, 2, … … · ‚T, (a) Show that variance of the usual OLS estimator (0² / Σ(x+ - x)²) underestimates the true variance of the OLS estimator. (b) The value of the Durbin-Watson statistic turned out to be 1.4. Compute an estimate of p, the serial correlation parameter, based on the value of the Durbin-Watson statistic. (c) Suppose you also wish to test for serial correlation using Durbin's alternative test (Durbin's h- test) at the 5 percent significance. After estimating the original regression on the entire 80 sam- ples, you saved the residuals and estimated the following auxiliary regression. Et = 0.07 + 0.08æt+ 0.3 êt_1 (0.04) (0.02) (0.1) (Standard errors are in parentheses.) Give the value of the test statistic, and your conclusion (accept or reject the null hypothesis of no serial correlation). (d) Regardless of your answers to parts (a)-(c), suppose you believe that…7. Suppose X has a Poisson distribution such that 3P(X = 1) = P(X = 2). a) Find P(X = 4) b) Find mean and variance of -10X + 15Move to Archive x 0.3e If 1-.7et is the mgf of a well known function. It is Geometric mgf i) Its name is ii) The mean of this distribution = iii) P(x = 4) = iv) The variance of this distribution isQ. 1 (i) Find moment generating functions (mgf) of the following probability distributions. (ii) Using mgf found in (i) above, find mean and variance. (i) fx(x;n,p) = {x)p*q"=*;_x= 0,1,2,-, n, 0; е. w. (e-^ax. x = 0,1,2,, (ii) fx(x; 2) = 0; x! е. W. 1 ( ii) fx (x; α, β) : r(a)ga x“-te¬x/B; 0 < x <∞ (iv) fx(x; ß) = e-x/B;0 < x< ∞ 1 (x-µ)²] (v) fx(x; µ, o) = To VER exp[- ;-00 < x< ∞ 2σ2 1 ( vi) fK (x; α, β) B(a,f) *"-(1 – x)*-1; 0 < x < 1 %3D Г(а)Г(В) where B(a,ß) = r(a+B) (vii) F<(x, a, f) = x«-lexp[-;)"]:04 Let f(x) = (1/10)(x-3)^2 for x = 1, 2, 3, 4, 5 %3D Find the standard deviation of X. For the instructor, this was question 11. / 1.8 X 3.1 X 3.4 X 3.5 X 9.4 X 12.4SEE MORE QUESTIONSRecommended textbooks for youMATLAB: An Introduction with ApplicationsStatisticsISBN:9781119256830Author:Amos GilatPublisher:John Wiley & Sons IncProbability and Statistics for Engineering and th…StatisticsISBN:9781305251809Author:Jay L. DevorePublisher:Cengage LearningStatistics for The Behavioral Sciences (MindTap C…StatisticsISBN:9781305504912Author:Frederick J Gravetter, Larry B. WallnauPublisher:Cengage LearningElementary Statistics: Picturing the World (7th E…StatisticsISBN:9780134683416Author:Ron Larson, Betsy FarberPublisher:PEARSONThe Basic Practice of StatisticsStatisticsISBN:9781319042578Author:David S. Moore, William I. Notz, Michael A. FlignerPublisher:W. H. FreemanIntroduction to the Practice of StatisticsStatisticsISBN:9781319013387Author:David S. Moore, George P. McCabe, Bruce A. CraigPublisher:W. H. FreemanMATLAB: An Introduction with ApplicationsStatisticsISBN:9781119256830Author:Amos GilatPublisher:John Wiley & Sons IncProbability and Statistics for Engineering and th…StatisticsISBN:9781305251809Author:Jay L. DevorePublisher:Cengage LearningStatistics for The Behavioral Sciences (MindTap C…StatisticsISBN:9781305504912Author:Frederick J Gravetter, Larry B. WallnauPublisher:Cengage LearningElementary Statistics: Picturing the World (7th E…StatisticsISBN:9780134683416Author:Ron Larson, Betsy FarberPublisher:PEARSONThe Basic Practice of StatisticsStatisticsISBN:9781319042578Author:David S. Moore, William I. Notz, Michael A. FlignerPublisher:W. H. FreemanIntroduction to the Practice of StatisticsStatisticsISBN:9781319013387Author:David S. Moore, George P. McCabe, Bruce A. CraigPublisher:W. H. Freeman