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106	 Chapter 2  Review of Probability

   computer and a computer program that can generate i.i.d. draws from the
   N(5, 100) distribution. Explain how you can use your computer to compute
   an accurate approximation for Pr(Y 6 3.6).

	 2.17	 Yi, i = 1, c, n, are i.i.d. Bernoulli random variables with p = 0.6. Let
                                  Y denote the sample mean.

	 a.	 Use the central limit to compute approximations for

   i.  Pr(Y 7 0.64) when n = 50.

                                       ii.  Pr(Y 6 0.56) when n = 200.

	 b.	 How large would n need to be to ensure that Pr(0.65 7 Y 7 0.55) = 0.95?
                                       (Hint: Use the central limit theorem to compute an approximate answer.)

	 2.18	 In any year, the weather may cause damages to a home. On a year-to-year

                                  basis, the damage is random. Let Y denote the dollar value of damages in

                                  any given year. Suppose that during 95% of the year Y = $0, but during
                                  the other 5% Y = $30,000.

	 a.	 What are the mean and standard deviation of damages caused in a
                                       year?

	 b.	 Consider an “insurance pool” of 120 people whose homes are suf-
                                       ficiently dispersed so that, in any year, the damage to different homes
                                       can be viewed as independently distributed random variables. Let Y
                                       denote the average damage caused to these 120 homes in one year.
                                       (i) What is the expected value of the average damage Y? (ii) What is
                                       the probability that Y exceeds $3,000?

	 2.19	 Consider two random variables X and Y. Suppose that Y takes on k values
                                  y1, c, yk and that X takes on l values x1, c, xl.

	  a.	 Show that Pr(Y = yj)            =  g  l  =  1Pr(Y  =  yj  ͉  X  =  xi) Pr(X  =  xi). [Hint:
                                             i

   Use the definition of Pr(Y = yj ͉ X = xi).]

	 b.	 Use your answer to (a) to verify Equation (2.19).

	 c.	 Suppose that X and Y are independent. Show that sXY = 0 and
                                       corr(X, Y) = 0.

	 2.20	 Consider three random variables X, Y, and Z. Suppose that Y takes on

   k values y1, c, yk, that X takes on l values x1, c, xl, and that Z takes
   on m values z1, c, zm. The joint probability distribution of X, Y, Z is
   Pr(X = x, Y = y, Z = z), and the conditional probability distribution of
                                                                       Pr(Y = y, X = x, Z =   z).
   Y given X and Z is Pr(Y = y ͉ X = x, Z = z)                      =       Pr(X = x, Z = z)
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