To understand the insurance, it is essential to understand the terms such as risk, peril, law of large numbers, law of average and the ‘theory of probability’.

Suppose there are one hundred date trees in a field. It is not possible that all the trees produce same number of dates. Neither the quality of each date in terms of weight, size and taste is same. It also happens that the same tree varies each year in giving the number of dates. If the average of each tree in a span of 5 years is calculated, and total number or weight of the dates divided by one hundred, the average production of the dates per tree can be obtained. This is called the law of average.

Probability can be defined simply as the relationship of the favorable cases over total number of cases, or calculated as: p=n/N.

A simple example of the theory of probability is that there are 10 balls in a jar; 5 of them are blue; then what will be the probability to extract one blue ball from the jar of 10? That means there are 5 cases in a total of 10 elements.
The probability is 5/10 = 0.5

The law of averages is used to express the view that ultimately, everything “evens out” and this is called the law of large numbers. For example, the longer one flips a coin, it is likely that number of heads and tails will equalize. When we toss the coin 1000 times, we would expect the result to be approximately 500 heads results, because this would reflect the underlying 0.5 probability (chance) of a heads results for any given flip.

In the case of large numbers, generally the average moves closer to the underlying probability (0.5), although in absolute terms deviation from the expected value will increase. For example, after 1000 coin flips, we might see 530 heads. After 10,000 flips, we might then see 5098 heads. The average has now moved closer to the underlying .5 probability, from .53 to .5098. However, the absolute deviation from the expected number of heads has gone up from 30 to 98.