1. There are at most 100 identical balls in a bowl but we don't know the exact number of them. However, we know that the balls are numbered with numbers 1, 2, ..., 0 and each of the number from number on to number 0 is used exactly once and the 0 ≥ 1 is an integer. We pick a single ball in random. Let Y be the number in a ball we pick at random. (a) What is the parameter space in the statistical model corresponding this setup? (b) What is the probability mass function f(y; 0) of the random variable Y? (c) Suppose that the obseverd number is = y 57. Tell what is the likelihood function corresponding to this data. What is the maximum likelihood estimate of the parameter with this observation. What is the maximum likelihood estimator of the parameter 0? (d) Show by calculating that the espected value of the maximum likelihood estima- tor (Y) is E(Y) = = 0 + 1 2 What is the bias of the ML estimator bias, (⑦(Y))? (Hint: the English Wikipedia page https://en.wikipedia.org/wiki/Discrete_uniform_distribution might be useful)

MATLAB: An Introduction with Applications
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Author:Amos Gilat
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Chapter1: Starting With Matlab
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1. There are at most 100 identical balls in a bowl but we don't know the exact number
of them. However, we know that the balls are numbered with numbers 1, 2, ..., 0
and each of the number from number on to number 0 is used exactly once and the
0 ≥ 1 is an integer. We pick a single ball in random. Let Y be the number in a ball
we pick at random.
(a) What is the parameter space in the statistical model corresponding this setup?
(b) What is the probability mass function f(y; 0) of the random variable Y?
(c) Suppose that the obseverd number is
=
y 57. Tell what is the likelihood function
corresponding to this data. What is the maximum likelihood estimate of the
parameter with this observation. What is the maximum likelihood estimator
of the parameter 0?
(d) Show by calculating that the espected value of the maximum likelihood estima-
tor (Y) is
E(Y) =
=
0 + 1
2
What is the bias of the ML estimator bias, (⑦(Y))? (Hint: the English Wikipedia
page https://en.wikipedia.org/wiki/Discrete_uniform_distribution might
be useful)
Transcribed Image Text:1. There are at most 100 identical balls in a bowl but we don't know the exact number of them. However, we know that the balls are numbered with numbers 1, 2, ..., 0 and each of the number from number on to number 0 is used exactly once and the 0 ≥ 1 is an integer. We pick a single ball in random. Let Y be the number in a ball we pick at random. (a) What is the parameter space in the statistical model corresponding this setup? (b) What is the probability mass function f(y; 0) of the random variable Y? (c) Suppose that the obseverd number is = y 57. Tell what is the likelihood function corresponding to this data. What is the maximum likelihood estimate of the parameter with this observation. What is the maximum likelihood estimator of the parameter 0? (d) Show by calculating that the espected value of the maximum likelihood estima- tor (Y) is E(Y) = = 0 + 1 2 What is the bias of the ML estimator bias, (⑦(Y))? (Hint: the English Wikipedia page https://en.wikipedia.org/wiki/Discrete_uniform_distribution might be useful)
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