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urgent solution for part c) and d) needed, thank you (25 pts) Central Limit Theorem. Let X1, X2, X3, be a sequence of i.i.d. random
urgent solution for part c) and d) needed, thank you
(25 pts) Central Limit Theorem. Let X1, X2, X3, be a sequence of i.i.d. random variables with finite mean u and finite variance o?, and let Zn be the mean of the first n random variables in the sequence: X1 + X2 + ... + Xn Zn n = (a) Let X, for i 1, 2, ... be a uniform continuous random variable taking values in the interval (3, 7). Write a MATLAB program to plot the pdf of Zn. Consider n=1, 2, 3, 10, 30, 100 and compare your results across different n's. (b) Calculate analytically the mean and the variance of X; and of Zn in part (a). (c) Write a MATLAB program to generate a Gaussian random variable with the same mean and variance as Zn. Superimpose its pdf on the plots from part (a). (d) Repeat parts (a), (b), and (c) with Xi representing a toss of a 5-sided that is described in Problem 1(d). Note that Xi and Zn are discrete in this case. Hint. You can calculate the PDF analytically or empirically. For the later method, use t = 104 samples and while plotting histogram for discrete data, use 'BinWidth' as n+1 (25 pts) Central Limit Theorem. Let X1, X2, X3, be a sequence of i.i.d. random variables with finite mean u and finite variance o?, and let Zn be the mean of the first n random variables in the sequence: X1 + X2 + ... + Xn Zn n = (a) Let X, for i 1, 2, ... be a uniform continuous random variable taking values in the interval (3, 7). Write a MATLAB program to plot the pdf of Zn. Consider n=1, 2, 3, 10, 30, 100 and compare your results across different n's. (b) Calculate analytically the mean and the variance of X; and of Zn in part (a). (c) Write a MATLAB program to generate a Gaussian random variable with the same mean and variance as Zn. Superimpose its pdf on the plots from part (a). (d) Repeat parts (a), (b), and (c) with Xi representing a toss of a 5-sided that is described in Problem 1(d). Note that Xi and Zn are discrete in this case. Hint. You can calculate the PDF analytically or empirically. For the later method, use t = 104 samples and while plotting histogram for discrete data, use 'BinWidth' as n+1Step by Step Solution
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