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If a coin were tossed in the air, there is a 50-50 chance that the coin will come up heads. Or if there is a container with 100 red balls and 100 green ones, and one ball were drawn at random, again there is a 50- 50 chance that a red one will be drawn. The greater the number of times a coin is tossed or a ball is drawn, the greater the regularity of the desired occurrence. Thus, when we have extremely large numbers, the law of average gives effect to a law of chance. A combination of a large number of uncertain-ties will result in relative certainty on the basis of the law of large numbers. From experience it can be shown that a certain number out of a given group of properties will be damaged or destroyed by some peril; or that a certain number of persons out of a select population will die at a given age; or out of a given number of automobiles on a highway a certain number will be damaged by accidents. The larger the number of exposures to a particular risk, the greater the accuracy of loss prediction. In other words, the law of large numbers is founded on the proposition that the reliance to be placed on a given probability is increased when the number of chances is increased. This approach relies on the relative-frequency of an observed outcome. In using the relative-frequency approach to probability, as the number of observations of events and their outcomes is increased, the accuracy of the probability figure based on these observations is increased.
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