Simple Probability

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Definition: Simple Probability


Simple Probability


Full Definition of Simple Probability


Simple probability is the calculation of a result or the likelihood of an event occurring. Insurance firms utilise probability statistics to calculate the likelihood of having to pay a claim.

A simple probability is computed by dividing a single event by the total number of possible outcomes. When flipping a coin, for example, there are two possible outcomes: heads or tails. To calculate the likelihood of receiving either heads or tails, divide one outcome (1) by the two possible outcomes (2). When you divide 1 by 2, you get .50, or 50%.

Because life is not as easy as a coin toss, insurance firms must consider far more than two outcomes. They do, however, employ the same fundamental formula to decide how much they will pay out to groups of policyholders who have the same sort of policy. This result informs them of the amount of money they will need to collect to offset their possible losses (the amount they payout).

Returning to the coin example, the 50/50 split that one would predict with a 50 per cent probability may not occur on the first two flips — it may land on heads twice, tails twice, and heads again. As a result, the likelihood of receiving one of the outcomes becomes less predictable. This is when the principle of huge numbers comes into play. According to the rule of large numbers, the more data points there are, the more accurate a result prediction will be. If you continue to flip the coin and record the results (say, 100 times or more), the chance will approach 50%.

To calculate the possibility of an event occurring, insurance companies engage actuaries, who are highly trained professionals in probability statistics and data analysis. Actuaries study and train for at least 6–10 years in order to forecast events more correctly.

The insurance company will evaluate the possibility of having to pay out on a specific type of claim based on the probability of the event (outcome). Based on these findings, the company calculates how much money it will need to collect in order to pay out the claims filed for that year. This money will be collected through insurance premiums.

If something is unlikely to occur, the insurance premium for one coverage will be less expensive than a claim for something more likely. For example, if a community has a history of hail, the premium for such coverage will most certainly be high. If the same municipality is located distant from significant bodies of water and streams, flood insurance will most likely be inexpensive.

Weighted probability is another notion used by actuaries. Because predicting life events frequently involves more than one or two factors (not just heads or tails), actuaries must consider not just the probable outcomes, but also the desired outcomes and the number of paths that can lead to those results.

Rolling one die, for example, the probability of rolling a two is the same as rolling a four: 1/6. However, by rolling two dice, there is a larger possibility of getting a four than a two. This is due to the fact that there is only one way to get two when using two dice (1, 1), whereas four can be scored with more than one combination (1, 3 or 2, 2 or 3, 1). This signifies that the likelihood of scoring four is weighted higher than the probability of scoring two.

Compute the total number of possible outcomes (total values) in the scenario to determine weighted probability. Then, figure out how many different outcomes are possible. Divide the number of possible outcomes by the number of ways to obtain the outcome.

Returning to the two dice example, the total number of possible outcomes is 36 (6 sides 6 sides = 36 options) when attempting to compute the weighted probability (per cent) of rolling a score of four with two dice. This role can be obtained in three ways (1, 3 or 2, 2 or 3, 1). The ultimate result is as follows:

3 desirable outcomes x 36 potential outcomes = 0.083 (approximately 8.3%)

Again, insurance companies consider a vast array of outcomes and methods for achieving those results when determining what is and is not covered, which is why they rely on highly qualified specialists to crunch the figures. The bottom conclusion is that insurance companies do not decide what is and is not covered at random. They do the math to ensure that they can maintain their financial health and protect their clients.


Related Phrases


Risk
Return on Policyholder Surplus
Surplus to Policyholders
Accident-Year Statistics
Mortality and Expense Risk Fees
Risk Class
Compound Probability
Experimental Probability


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Definition Sources


Definitions for Simple Probability are sourced/syndicated and enhanced from:

  • A Dictionary of Economics (Oxford Quick Reference)
  • Oxford Dictionary Of Accounting
  • Oxford Dictionary Of Business & Management

This glossary post was last updated: 20th January, 2022 | 2 Views.