Consider a random sample X1, … , Xn from the pdf f (x; u) = .5(1 + (THETA)x) -1 <= x <= 1 where -1 <= theta <= 1 (this distribution arises in particle physics). Show that theta = 3X is an unbiased estimator of theta. [Hint: First determine mu = E(X) = E(X).]
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Consider a random sample X1, … , Xn from the pdf
f (x; u) = .5(1 + (THETA)x) -1 <= x <= 1
where -1 <= theta <= 1 (this distribution arises in particle
physics). Show that theta = 3X is an unbiased estimator of
theta. [Hint: First determine mu = E(X) = E(X).]
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- Consider the following two formulations of the bivariate PRF, where ui and εi are both mean-0 stochastic disturbances (i.e random errors): yi = β0 + β1xi + u yi = α0 + α1(xi − x¯) + ϵ a) Write the OLS estimators of β1 and α1. Are the two estimators the same? b) What is the advantage, if any, of the second model over the first?If X1 and X2 constitute a random sample of size n = 2from an exponential population, find the efficiency of 2Y1relative to X, where Y1 is the first order statistic and 2Y1and X are both unbiased estimators of the parameterLet X be a Poisson random variable with E(X) = 3. Find P(2 < x < 4).
- Based on the following values: Mathematical expectation: E(X) = ∑Xn1 = 1204 = 30 E(Y) = ∑Yn2 = 1884 = 47 E(Z) = ∑Zn3 = 1784 = 44.5 Variance: var(X) = 1n1-1∑X2-1n∑X2 = 14-13678-12024 =26 var(Y) = 1n2-1∑Y2-1n∑Y2 = 14-18890-18824 =18 var(Z) = 1n3-1∑Z2-1n3∑Z2 = 14-18322-17824 =133.6667 Root mean square deviation sd(X)= var(X) =26 = 5.0990 sd(Y)= var(Y) =18 = 4.2426 sd(Z)= var(Z) =133.6667 = 11.5614 Correlation coefficients X Y Z 25 44 28 28 43 48 37 49 55 30 52 47 1. Expectation 120 188 178 2. Variance 26 18 133.6667 3. root mean square deviation 5.099 4.2426 11.5614 Check the hypotheses in the image below, in accordance with the tablic values.Based on the following values: Mathematical expectation: E(X) = ∑Xn1 = 1204 = 30 E(Y) = ∑Yn2 = 1884 = 47 E(Z) = ∑Zn3 = 1784 = 44.5 Variance: var(X) = 1n1-1∑X2-1n∑X2 = 14-13678-12024 =26 var(Y) = 1n2-1∑Y2-1n∑Y2 = 14-18890-18824 =18 var(Z) = 1n3-1∑Z2-1n3∑Z2 = 14-18322-17824 =133.6667 Root mean square deviation sd(X)= var(X) =26 = 5.0990 sd(Y)= var(Y) =18 = 4.2426 sd(Z)= var(Z) =133.6667 = 11.5614 Correlation coefficients X Y Z 25 44 28 28 43 48 37 49 55 30 52 47 1. Expectation 120 188 178 2. Variance 26 18 133.6667 3. root mean square deviation 5.099 4.2426 11.5614 Check the hypothesis in the image below. The table values are also thereBased on the following values: Mathematical expectation: E(X) = ∑Xn1 = 1204 = 30 E(Y) = ∑Yn2 = 1884 = 47 E(Z) = ∑Zn3 = 1784 = 44.5 Variance: var(X) = 1n1-1∑X2-1n∑X2 = 14-13678-12024 =26 var(Y) = 1n2-1∑Y2-1n∑Y2 = 14-18890-18824 =18 var(Z) = 1n3-1∑Z2-1n3∑Z2 = 14-18322-17824 =133.6667 Root mean square deviation sd(X)= var(X) =26 = 5.0990 sd(Y)= var(Y) =18 = 4.2426 sd(Z)= var(Z) =133.6667 = 11.5614 Correlation coefficients X Y Z 25 44 28 28 43 48 37 49 55 30 52 47 1. Expectation 120 188 178 2. Variance 26 18 133.6667 3. root mean square deviation 5.099 4.2426 11.5614 Check the hypothesis in the images. The table values are in the other image below
- Based on the following values: Mathematical expectation: E(X) = ∑Xn1 = 1204 = 30 E(Y) = ∑Yn2 = 1884 = 47 E(Z) = ∑Zn3 = 1784 = 44.5 Variance: var(X) = 1n1-1∑X2-1n∑X2 = 14-13678-12024 =26 var(Y) = 1n2-1∑Y2-1n∑Y2 = 14-18890-18824 =18 var(Z) = 1n3-1∑Z2-1n3∑Z2 = 14-18322-17824 =133.6667 Root mean square deviation sd(X)= var(X) =26 = 5.0990 sd(Y)= var(Y) =18 = 4.2426 sd(Z)= var(Z) =133.6667 = 11.5614 Correlation coefficients X Y Z 25 44 28 28 43 48 37 49 55 30 52 47 1. Expectation 120 188 178 2. Variance 26 18 133.6667 3. root mean square deviation 5.099 4.2426 11.5614 Check the hypothesis in the image below. The tablic values are also thereA snack food manufacturer estimates that the variance of the number of grams of carbohydrates in servings of its tortilla chips is 1.33. A dietician is asked to test this claim and finds that a random sample of 24 servings has a variance of 1.37. At α=0.01, is there enough evidence to reject the manufacturer's claim? Assume the population is normally distributed. Complete parts (a) through (e) below. (a) Write the claim mathematically and identify H0 and Ha. A. H0: σ2≤1.33 (Claim) Ha: σ2>1.33 B. H0: σ2≠1.33 Ha: σ2=1.33 (Claim) C. H0: σ2≥1.33 Ha: σ2<1.33 (Claim) D. H0: σ2=1.33 (Claim) Ha: σ2≠1.33 (b) Find the critical value(s) and identify the rejection region(s). The critical value(s) is(are) enter your response here. (Round to two decimal places as needed. Use a comma to separate answers as needed.) Choose the correct statement below and fill in the corresponding answer boxes. A. The…Suppose X1, X2, X3, X4 be i.i.d. normal random variables with mean 0 and variance sigma^2, where sigma^2 is the unknown parameter. Consider the following estimators: T1 = X1 - X2 + X4, T2 = 1/3(X1 + X1 + X4), T3... T4... T5 = 1/2|X1 - X2| (a) Is T1 unbiased for sigma^2, for i = 1,2,3,4 (b) Among the estimators T1,...,T4 for sigma^2, which has the smallest MSE? (c) Is T5 unbiased for sigma? If not, find a constant k so that k*T5 is unbiased for sigma^2. Evaluate the MSE of T5.
- Suppose a linear model y=β0+β1xy=β0+β1x is fit to a sample data set, and a test of the null hypothesis H0:β1=0H0:β1=0 against an alternative hypothesis HA:β1≠0HA:β1≠0 is performed; a PP-value of 0.4203 is obtained. Which of the following scatter plots depicts the data set on which this model was fit and the hypothesis test was performed?9.1) Suppose X1, X2, and X3, denotes a random sample from the exponential distribution with density function shown in the image. a) Which of the above estimators are unbiased for θ? b) Among the unbiased estimators of θ, which has the smallest variance?a hypothesis test produces a t statistic of t=2.3. if the researcher is using a two tailed test with a=0.05 how large does the sample have to bw in order to reject the null hypothesis?