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This question is to help you understand the idea of a sampling dis- tribution. Let Xi, , xn be IID with mean μ and variance σ2. Let Xi. Then Xn is a statistic, that is, a function of the data. Since Xn is a random variable, it has a distribution. This distri- bution is called the sampling distribution of the statistic. Recall from Theorem 3.17 that E(Xn) μ and V(Xn) σ2/n. Dont confuse the distribution of the data fx and the distribution of the statistic fx.. To make this clear, let X1,... , Xn ~Uniform(0,1). Let fx be the density of the Uniform (0, 1) . Plot Íx . Mow let Xn-n-ı ΣΊ xi. Find E(X,) and V(Xn). Plot them as a function of n. Interpret. Now simulate the distribution of Xn for n- 1,5,25, 100. Check that the simulated values of E(Xn) and V(Xm) agree with your theoretical calculations. What do you notice about the sampling distribution of Xn as n increases? TL

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