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Let {Xi} be i.i.d. Exp(A). Define X = Xi. Modify the Python code at the link below to do the following problems (if you like, you can program in another language, such as Matlab): https://trinket.io/python3/da689a5760 a) For A = 1, compute C1-1(X) for n âˆˆ {10, 100, 1000, 10000, 100000, 1000000}. Compare to E[X]. b) Repeat part (a) for A = 0.5. c) For A = 1, compute E[Z-1(1/X; 2^(1/4))] for n âˆˆ {10, 100, 1000, 10000, 100000, 1000000}. Compare to P[X â‰¥ 1/A]. Here we define the indicator function: if X â‰¥ 1/A, then 1(X â‰¥ 1/A) = 1; else 1(X â‰¥ 1/A) = 0. Repeat part (c) for A = 0.5. Compute E[X|X > 1/4]. Describe how you would write a computer program (with, say, a million i.i.d. exponentially distributed random variables) to verify this empirically: Write the program and verify it empirically and present your results.

          Let {Xi} be i.i.d. Exp(A). Define X = Xi. Modify the Python code at the link below to do the following problems (if you like, you can program in another language, such as Matlab): https://trinket.io/python3/da689a5760

a) For A = 1, compute C1-1(X) for n âˆˆ {10, 100, 1000, 10000, 100000, 1000000}. Compare to E[X].
b) Repeat part (a) for A = 0.5.
c) For A = 1, compute E[Z-1(1/X; 2^(1/4))] for n âˆˆ {10, 100, 1000, 10000, 100000, 1000000}. Compare to P[X â‰¥ 1/A]. Here we define the indicator function: if X â‰¥ 1/A, then 1(X â‰¥ 1/A) = 1; else 1(X â‰¥ 1/A) = 0.
Repeat part (c) for A = 0.5. Compute E[X|X > 1/4].

Describe how you would write a computer program (with, say, a million i.i.d. exponentially distributed random variables) to verify this empirically: Write the program and verify it empirically and present your results.

let xi81 be iid expa define x xi modify the python code at the link below t0 do the following problems if you like you can program in another language such as matlab httpsiltrinket iolpython 26189

Added by Joseph N.

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