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You observe k i.i.d. copies of the discrete uniform random variable Xi , which takes values 1 through n with equal probability....Asked by Stats NErd
You observe k i.i.d. copies of the discrete uniform random variable Xi , which takes values 1 through n with equal probability.
Define the random variable M as the maximum of these random variables, M=maxi(Xi) .
1.) Find the probability that M≤m , as a function of m , for m∈{1,2,…,n} .
2.) Find the probability that M=1 .
3.) Find the probability that M=m for m∈{2,3,…n} .
4.) For n=2 , find E[M] and Var(M) as a function of k .
5.) As k (the number of samples) becomes very large, what is E[M] in terms of n ?
As k→∞ , E[M]→
Define the random variable M as the maximum of these random variables, M=maxi(Xi) .
1.) Find the probability that M≤m , as a function of m , for m∈{1,2,…,n} .
2.) Find the probability that M=1 .
3.) Find the probability that M=m for m∈{2,3,…n} .
4.) For n=2 , find E[M] and Var(M) as a function of k .
5.) As k (the number of samples) becomes very large, what is E[M] in terms of n ?
As k→∞ , E[M]→
Answers
Answered by
Finn
1. (m/n)^k
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