e called switches with stored program control (SPC). The LCD category may be broken down into three subcategories, depending on how the queue or pool of waiting calls is handled. The waiting calls may be handled last in first out, first in first out, or at random. 4.2.1.2.3 Infinite and Finite Traffic Sources. We can assume that traffic sources are either infinite or finite. For the infinite-traffic-sources case the probability of call arrival is constant and does not depend on the occupancy of the system. It also implies an infinite number of call arrivals, each with an infinitely small holding time. An example of finite traffic sources is when the number of sources offering traffic to a group of trunks is comparatively small in comparison to the number of circuits. We can also say that with a finite number of sources the arrival rate is proportional to the number of sources that are not already engaged in sending a call 4.2.1.2.4 Probability-Distribution Curves. Telephone-call originations in any particu- lar area are random in nature. We find that originating calls or call arrivals at an exchange closely fit a family of probability-distribution curves following a Poisson5 distribution. The Poisson distribution is fundamental in traffic theory Most probability-distribution curves are two-parameter curves; that is, they may be described by two parameters: mean and variance. The mean is a point on the probability- distribution curve where an equal number of events occur to the right of the point as to the left of the point. Mean is synonymous with average. Consult Figure 4.3. The second parameter used to describe a distribution curve is the dispersion, which tells us how the values or population are dispersed about the center or mean of the curve. There are several measures of dispersion. One is the familiar standard deviation. Superscript(5). D. Poisson was a nineteenth-century French mathematician/physicist specializing in "randomness." 4.2 TRAFFIC INTENSITY DEFINES THE SIZE OF SWITCHES AND THE CAPACITY OF TRAN