Chapter 4: Q. 4.31 (page 172)
A jar contains chips, numbered . A set of size is drawn. If we let denote the number of chips drawn having numbers that exceed each of the numbers of those remaining, compute the probability mass function of .
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Chapter 4: Q. 4.31 (page 172)
A jar contains chips, numbered . A set of size is drawn. If we let denote the number of chips drawn having numbers that exceed each of the numbers of those remaining, compute the probability mass function of .
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Let X represent the difference between the number of heads and the number of tails obtained when a coin is tossed n times. What are the possible values of X?
For a hypergeometric random variable, determine
From a set of n elements, a nonempty subset is chosen at random in the sense that all of the nonempty subsets are equally likely to be selected. Let X denote the number of elements in the chosen subset. Using the identities given in Theoretical Exercise of Chapter, show that
Show also that for n large,
in the sense that the ratio Var(X) ton/approaches as n approaches q. Compare this formula with the limiting form of Var(Y) when P{Y =i}=/n,i=,...,n.
Consider coins, each of which independently comes up heads with probability . Suppose that is large and is small, and let . Suppose that all coins are tossed; if at least one comes up heads, the experiment ends; if not, we again toss all coins, and so on. That is, we stop the first time that at least one of the coins come up heads. Let denote the total number of heads that appear. Which of the following reasonings concerned with approximating is correct (in all cases, is a Poisson random variable with parameter ?
(a) Because the total number of heads that occur when all coins are rolled is approximately a Poisson random variable with parameter ,
(b) Because the total number of heads that occur when all coins are rolled is approximately a Poisson random variable with parameter , and because we stop only when this number is positive,
(c) Because at least one coin comes up heads, will equal 1 if none of the other coins come up heads. Because the number of heads resulting from these coins is approximately Poisson with mean ,
The random variable X is said to have the Yule-Simons distribution if
(a) Show that the preceding is actually a probability mass function. That is, show that
(b) Show that E[X] = 2.
(c) Show that E[X2] = q
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