B four cards are selected at random without

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Unformatted text preview: 51 cards, and we observe that this card is a diamond. Given this information, find the probability that the lost card is a club. b. Four cards are selected at random without replacement from the 51 cards, and we observe that all are hearts. Given this information, find the probability that the lost card is a club. 13 Example 7 Suppose that P (X = 0) = 1 − P (X = 1). If E (X ) = 3Var(X ), find: a. P (X = 0). b. V ar(3X ). Example 8 Let X ∼ b(n, p). Show that V ar(X ) = np(1 − p). Hint: First find E [(X (X − 1)] and then use σ 2 = EX 2 − µ2 . Example 9 Let X be a geometric random variable with probability of success p. The probability mass function of X is: P (X = k ) = (1 − p)k−1 p, k = 1, 2, · · · Show that the probabilities sum up to 1. Example 10 In a game of darts, the probability that a particular player aims and hits treble twenty with one dart is 0.40. How many throws are necessary so that the probability of hitting the treble twenty at least once exceeds 90%? Example 11 Show that the mean and variance of the hypergeometric distribution are: µ= nr N σ2 = nr(N − r)(N − n) N 2 (N − 1) Example 12 Using steps similar to those employed to find the mean of the binomial distribution show that the mean of the r negative binomial distribution is µ = p . Also show that the variance of the negative binomial distribution r1 2 is σ = p ( p − 1) by first evaluating E [X (X + 1)]. Example 13 r Show that if we let p = N , the mean and the variance of the hypergeometric distribution can be written as 2 µ = np and σ = np(1 − p) N −n . What does this remind you? N −1 Example 14 Suppose 5 cards are selected at random and without replacement from an ordinary deck of playing cars. a. Construct the probability distribution of X , the number of clubs among the five cards. b. Use (a) to find P (X ≤ 1). Example 15 The manager of an industrial plant is planning to buy a new machine of either type A, or type B . The number of daily repairs XA required to maintain a machine of type A is a random variable with mean and variance both equal to 0.10t, where t denotes the number of hours of daily operation. The number of daily repairs XB for a machine of type B is a random variable with mean and variance both equal 0.12t. The daily 2 2 cost of operating A is CA (t) = 10t + 30XA , and for B is CB (t) = 8t + 30XB . Assume that the repairs take negligible time and that each night the machines are tuned so that they operate essentially like new machines at the start of the next day. Which machine minimizes the expected daily cost if a workday consists of a. 10 hours b. 20 hours 14 Discrete random variables - some examples (solutions) Example 1 Let X be the payoff: Card X ($) P (X ) 4 Jack 15 52 4 Queen 15 52 4 King 5 52 4 Ace 5 52 36 Else -4 52 Therefore the expected gain is: 4 4 4 4 E (X ) = 15 52 + 15 52 + 5 52 + 5 52 − 4 36 = $ 16 . 52 52 Example 2 This is hypergeometric problem. The probability of accepting the lot is the pr...
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This note was uploaded on 10/04/2012 for the course STATISTICS 100a taught by Professor Cristou during the Spring '10 term at UCLA.

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