Posted: Wednesday, December 11, 2013 9:23 PM
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The probability of loss and the degree of uncertainty in relation to the law of large numbers is illustrated as follows: If out of 100,000 lives an average of 10 per thousand die each year, the probability of death is 1/100,000 or .001. If the number of risks were increased to 1,000,000, the degree of probability remains at .001. However, where the number of risks involved were 1,000,000 instead of 100,000, the degree of uncertainty is considerably less since there will be a relatively smaller variation from the average where the number of exposures is increased. When the probability is zero or small, uncertainty is likewise zero or small, and there is no chance or little chance. Uncertainty, however, increases only up to a certain point. The uncertainty is greatest when the chances are even, and then diminishes as the chances increase, until the uncertainty disappears, when the probability of occurrence becomes infinite. Probability experiences of the past are used in insurance to predict (within limits) the probability that an event will occur in the future. This assumes that the number of observations are large enough to give a dependable average, and that the future will parallel the past. Loss Measurements When the probability distribution of a loss is known, estimates can be made concerning whether some dollar loss will be incurred; the probability that severe losses might occur; the average loss per year; and the variation in possible results. A probability distribution lists all possible outcomes in a set, along with the probability that each event will occur. Assume that there are six buildings with the following probability distributions:
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• Location: Allentown, Allentown PA
• Post ID: 12840219 allentown