Page 75 - Probability, Random Variables and Random Processes
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CHAP.  21                        RANDOM  VARIABLES







                  Note that by setting a = ka,  in Eq. (2.97), we obtain



               Equation (2.98) says that the probability that a r.v. will fall k or more standard deviations from its mean is
               < l/k2. Notice that nothing at all is said about the distribution function of X. The Chebyshev inequality is
               therefore quite a generalized statement. However, when applied to a particular case, it may be quite weak.




         SPECIAL  DISTRIBUTIONS
         2.37.  A binary source generates digits 1 and 0 randomly with probabilities 0.6 and 0.4, respectively.
               (a)  What is the probability that two 1s and three 0s will occur in a five-digit sequence?
               (b)  What is the probability that at least three 1s will occur in a five-digit sequence?
               (a)  Let X be the r.v. denoting the number of  1s generated in a five-digit sequence. Since there are only two
                  possible outcomes (1 or O),  the  probability  of  generating  1 is constant, and there are five digits, it is
                  clear that  X  is a  binomial  r.v.  with  parameters (n, p) = (5, 0.6). Hence, by  Eq. (2.36), the probability
                  that two  1s and three 0s will occur in a five-digit sequence is


               (b)  The probability that at least three 1s will occur in a five-digit sequence is



                  where

                  Hence,                   P(X 2 3) = 1 - 0.317 = 0.683


         2.38,  A fair coin is flipped 10 times. Find the probability of the occurrence of  5 or 6 heads.
                  Let the r.v. X denote the number of heads occurring when  ia fair coin is flipped 10 times. Then X is a
               binomial r.v. with parameters (n, p) = (10, 4). Thus, by Eq. (2.36),






         2.39.  Let X be a binomial  r.v. with parameters (n, p), where 0 <: p < 1. Show that as k goes from 0 to
               n, the pmf p,(k)  of X first increases monotonically and then decreases monotonically, reaching its
               largest value when k is the largest integer less than or equal to (n + 1)p.
                  By Eq. (2.36), we have







               Hence, px(k) 2 px(k - 1) if  and  only  if  (n - k + l)p 2 k(l - p)  or  k I  (n + 1)p. Thus,  we  see  that  px(k)
               increases  monotonically  and  reaches  its  maximum  when  k  is  the  largest  integer  less  than  or  equal  to
               (n + 1)p and then decreases monotonically.
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