Suppose the random variable, X, follows an exponential distribution with mean 8 (0 ≤0<∞o). Let X₁, X₂, X, be a random sample of size n from the population of X.(d) Let 6 = 2 and n = 1. Determine the value of k (that is used in the specification ofthe rejection region) so that a = 0.05.(e) If Y₁, Y... Ym is a random sample from another exponential distribution withmean 6, find the likelihood ratio criterion for testing Ho: 0= 6 versus H₁ : 06.(Note here you need to use both samples-X₁, X₂, X and Y₁, Y2,... Ym to testthe equality of the two population means.)(f) Using the sampling distributions of inX and my under Ho: 0= 6, show that theabove test in part (e) is based on an F statistic. [Hint: Both statistics follow x²distributions independently.]

Random variable X follows exponential distribution with mean Random variable X follows exponential…

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A First Course in Probability (10th Edition)

10th Edition

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Author:Sheldon Ross

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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...

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If we let X1, X2,...X10 be a random sample from the distribution N( μ, σ), then what is the value k so that: P( (X-μ)/(σ/√10) < k ) = .05 P( (X-μ)/(S/√10) < k ) = .05 P( k < (X-μ)/(S/√10) ) = .05
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Suppose you have a random sample of observations from random variables Xi, i=1, 2, .., n. Assume that X;'s are identically distributed and they have the following distribution function: f(x;;0) =o* (1–ơ), x; = 1,2 , 3., 0
Assume that n independent count variables {X,,X2,...,X,} are identically distributed as X, ~ Poi(0) where i= 1,2,...,n and to estimate E(X,)= 0, consider the sample mean estimator ô = -5x,. n (b) Use the expectation of the distribution of S = nô to compute the expectation E(@) and the bias of this estimator. State whether this estimator unbiased. (c) Use the variance of the distribution of S= nô to examine var(Ô) and the standard error of this estimator. Use the variance and the bias of ê to compute the Mean Squared Error (MSE) of this estimator. Comment on the MSE behaviour in the asymptotic limit as n→o. State whether this estimator is consistent or (d) not.
Let X1, X2,...X, be a random sample from f(x,e) = -.0 < x< 8, then T= max(X,} is a %3D complete statistic for the parameter 0 Select one: O True False
Consider again the random variable with a cumulative distribution function ofF(x) = x^2/25, for 0 ≤ x ≤ 5. (d) What is the probability of x =1? (e) Do you think x is a symmetric random variable? Why or why not? I need answers of sub-parts (d) and (e) only.
Please help me with this questions. thank you!
50. Let X₁, X2, ..., X50 be i.i.d. with E(X) = 25 and V(X₂) = 10. Consider the random variable defined by 50 X₁ the sample average X = Σ Apply the Central Limit Theorem to answer the following: n i=1 (a) What is the approximate distribution of X (include parameter(s))? (b) Approximate P(X> 25.5). (c) Approximate P(|X-25 <0.8). (d) Approximate the 0.975 quantile (97.5th%tile) of X.
If we assume that the distribution of means is normal, then 95% of all sample means a) will fall in the interval m ± 1.96(σm) b) will fall in the interval m ± 1.645(σm) c) will be no more than 1.645(σm) from μ d) will be no more than from 1.96(σm) from μ
4
A simple random sample of size n =66, is obtained from a population that is skewed left with =33 and =3. . Does the population need to be normally distributed for the sampling distribution of x to be approximately normally distributed? Why? What is the sampling distribution of x? Does the population need to be normally distributed for the sampling distribution of x to be approximately normally distributed? Why?(A) Yes. The central limit theorem states that the sampling variability of nonnormal populations will increase as the sample size increases. (B) Yes. The central limit theorem states that only for underlying populations that are normal is the shape of the sampling distribution of x normal, regardless of the sample size, n. (C)No. The central limit theorem states that only if the shape of the underlying population is normal or uniform does the sampling distribution of x, become approximately normal as the sample size, n, increases. (D) No. The central limit theorem…
Q4: Let i denote the mean of a random sample of size 25 from a gamma type distribution with a = 4 and p > 0. Then 1. 1. E(x) = 48 and Var(x) = 48² O True O False 2. I~N (4B, 4B²) 25 2. O True O False

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