ans Theorem 9.3. Let X and Y be independent random variables with finite variances, and a, b ER. Then Var(aX) = a²Var (X), Var (X + Y) = VarX + Var Y, Var (ax + bY) = a²VarX+ b²Var Y.
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- Let X 1 be a normal random variable with mean 2 and variance 3 and let X 2 be a normal random variable with mean 1 and variance 4. Assume that X 1 and X 2 are independent.(a) What is the distribution of the linear combination Y = 2X 1 + 3X 2 ?(b) What is the distribution of the linear combination Y = X 1 − X 2 ?Inspection trials are carried out in a factory to assess the quality of products. In each trial r¡ products are tested and Y;, the number of satisfactory items in the trial, is assumed to follow the binomial model Y; Bin(ri, p), where p is the proportion of satisfactory items in the production process. Using inspection data (rı, yı), (r2, Y2), …‚ (˜n, Yn) and assuming independent trials, the following log-likelihood for p was obtained ... l(p; data) = 25.8392 + 35 · log(p) + 17 · log(1 − p). A) Determine which of the following (r1, y₁), (r2, y2), …‚ (˜n, yn) is the correct data that yields the given log-likelihood 1(p; data). Note that you do not need to develop the likelihood from scratch, but to carefully look and use results shown in lectures, notes and exercises. B) Write the maximum likelihood estimate p.Let Y1, Y2, ... Yn be n independent random variables. E(Yi) = μ and Var(Yi) = o² for every 1 = 1,2, ... n (NOTE: W is the sample mean) Let W = 1 yi n n (a) (b) Find E(W). Find Var(W).
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