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52                     Fundamentals of Probability and Statistics for Engineers

           discrete. Let X  and Y  be two discrete random variables that assume at most
           a countably infinite number of value pairs (x i , y j ), i, j ˆ  1, 2, .. ., with nonzero
           probabilities. The jpmf of X and Y  is defined by

                               p  …x; y†ˆ P…X ˆ x \ Y ˆ y†;             …3:20†
                                XY

           for  all x  and  y.  It  is zero  everywhere except  at  points  (x i , y j ), i, j ˆ  1, 2,.. .,
                                                                     ˆ
           where it  takes values equal to  the joint  probability  P(X ˆ  x i  \  Y   y j ).  We
           observe the following properties, which are direct extensions of those noted in
           Equations (3.4), (3.6), and (3.7) for the single-random-variable case:

                                           _           9
                                  0 < p  …x i ; y j †  1;
                                       XY              >
                                                       >
                                                       >
                                                       >
                                X X                    >
                                      p  …x i ; y j †ˆ 1;  >
                                                       >
                                       XY              >
                                                       >
                                 i  j                  >
                                                       >
                                                       =
                                                                        …3:21†
                                   X
                                      p
                                       XY  …x i ; y†ˆ p …y†; >
                                                  Y
                                                       >
                                     i                 >
                                                       >
                                                       >
                                                       >
                                   X
                                                       >
                                      p XY  …x; y j †ˆ p …x†; >
                                                       >
                                                  X
                                                       >
                                                       >
                                    j                  ;
           where p (x) and p (y) are now called marginal probability mass functions. We
                 X
                          Y
           also have
                                        i:x i  x j:y j  y
                                         X X
                              F XY …x; y†ˆ       p  …x i ; y j †:       …3:22†
                                                  XY
                                         iˆ1  jˆ1
             Example 3.5. Problem: consider a simplified version of a two-dimensional
           ‘random walk’ problem. We imagine a particle that moves in a plane in unit
           steps starting from the origin. Each step is one unit in the positive direction, with
           probability p along the x axis and probability q ( p ‡  q ˆ  1) along the y axis. We
           further assume that each step is taken independently of the others. What is the
           probability distribution of the position of this particle after five steps?
             Answer: since the position is conveniently represented by two coordinates,
           we  wish  to  establish  p XY  (x, y)  where  random  variable  X  represents  the  x
           coordinate of the position after five steps and where Y  represents the y coord-
           inate. It is clear that jpmf p XY   (x, y) is zero everywhere except at those points
           satisfying  x ‡  y ˆ  5  and  x, y    0.  Invoking  the  independence  of  events  of
           taking successive steps, it follows from Section 3.3 that p  (5, 0), the probabil-
                                                           XY
           ity of the particle being at (5, 0) after five steps, is the product of probabilities of
           taking five successive steps in the positive x direction. Hence
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