Distributed random variables

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Reference no: EM13748

1. Daily Airlines fies from Amsterdam to London every day. The price of a ticket for this extremely popular flight route is $75. The aircraft has a passenger capacity of 150. The airline management has made a policy to sell 160 tickets for this fight in order to protect themselves against noshow passengers. Experience has shown that the probability of a passenger being a no-show is equal to 0:1. The booked passengers act independently of each other. Given this overbooking strategy, what is the probability that some passengers will have to be bumped from the fight?

2. Find an example in which three random variables are pairwise independent but not independent as a family.

3. Suppose that X and Y are two dependent random variables. In statistical applications, it is often the case that we can observe the random variable X but we want to know the dependent random variable Y . What is the best linear predictor of Y with respect to X? In other words, for which linear function y = α + β x is 

93_Distributed random variables.png

minimal? Express your answer in terms of: μX = E(X), μY = E(Y ), σX = √Var(X), σY = √Var(Y ), and ρXY = ρ(X; Y).

4. Let X and Y have joint mass function

1960_Distributed random variables1.png

where a is a constant. Find c, P(X = j), P(X + Y = r), and E(X).

5. Let X1, X2, be identically distributed random variables with mean ,and let N be a random variable taking values in the non-negative integers and independent of the Xi. Let S = X1 + X2 +    + XN. Show that E(S) = N, and deduce that E(S) = μE(N).

6. A factory has produced n robots, each of which is faulty with probability Φ. To each robot a test is applied which detects the fault (if present) with probability . Let X be the number of faulty robots, and Y the number detected as faulty. Assuming the usual independence, show that

1803_Distributed random variables2.png

Reference no: EM13748

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