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Random Variables and Probability Distributions                   73

               Assume that X  and Y  are independent. Determine P(X    25    Y  >  8), the prob-
                                                              \
               ability that the next earthquake within 50 miles will have a magnitude greater than
               8 and that its epicenter will lie within 25 miles of the nuclear plant.
           3.23  Let random variables X  and Y  be independent and uniformly distributed in the
               square (0, 0) <  (X , Y ) <  (1, 1). Determine the probability that XY  <  1/2.
           3.24 In splashdown maneuvers, spacecrafts often miss the target because of guidance
               inaccuracies, atmospheric disturbances, and other error sources. Taking the origin
               of the coordinates as the designed point of impact, the X  and Y  coordinates of the
               actual impact point are random, with marginal density functions
                                     1      2  2
                            f …x†ˆ       e  x =2   ;   1 < x < 1;
                             X         1=2
                                    …2 †
                                     1     2  2
                            f …y†ˆ     1=2 e  y =2   ;   1 < y < 1:
                             Y
                                    …2 †
               Assume that the random variables are independent. Show that the probability
               of  a  splashdown  lying  within  a  circle  of  radius  a  centered  at  the  origin
                      2
               is 1   e  a /2  2 .
           3.25  Let  X 1 , X 2 , ..., X n  be independent  and  identically distributed  random  variables,
               each with PDF  F X  (x). Show that

                                                             n
                          P‰min…X 1 ; X 2 ; ... ; X n †  uŠˆ 1  ‰1   F X …u†Š ;
                                                       n
                          P‰max…X 1 ; X 2 ; ... ; X n †  uŠˆ‰F X …u†Š :
               The above are examples of extreme-value distributions. They are of considerable
               practical importance and will be discussed in Section 7.6.
           3.26 In studies of social mobility, assume that social classes can be ordered from 1
               (professional) to 7 (unskilled). Let random variable X k  denote the class order of the
               kth generation. Then, for a given region, the following information is given:
               (i)  The pmf of X 0 is described by p 91) ˆ 0:00, p 92) ˆ 0:00, p 93) ˆ 0:04,
                                            X 0         X 0        X 0
                   p 94) ˆ 0:06, p 95) ˆ 0:11, p 96) ˆ 0:28, and p 97) ˆ 0:51.
                    X 0        X 0         X 0           X 0
               (ii)  The conditional probabilities P9X k‡1 ˆ ijX k ˆ j) for i, j ˆ 1, 2, ... , 7  and for
                   every k are given in Table 3.2.


                          Table 3.2 P9X k‡1 ˆ ijX k ˆ j)  for Problem 3.26
           i                                   j
                 1        2         3        4         5        6         7

           1     0.388    0.107     0.035    0.021     0.009    0.000     0.000
           2     0.146    0.267     0.101    0.039     0.024    0.013     0.008
           3     0.202    0.227     0.188    0.112     0.075    0.041     0.036
           4     0.062    0.120     0.191    0.212     0.123    0.088     0.083
           5     0.140    0.206     0.357    0.430     0.473    0.391     0.364
           6     0.047    0.053     0.067    0.124     0.171    0.312     0.235
           7     0.015    0.020     0.061    0.062     0.125    0.155     0.274








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