What is Unconditional Probability

An unconditional probability is the independent chance that a single outcome results from a sample of possible outcomes. The term refers to the likelihood that an event will take place independent of whether any other events take place or any other conditions are present. The probability that snow will fall in Jackson, Wyoming on Groundhog Day, without taking into consideration the historical weather patterns and climate data for northwestern Wyoming in early February is an example of an unconditional probability.

BREAKING DOWN Unconditional Probability

The unconditional probability of an event can be determined by adding up the outcomes of the event and dividing by the total number of possible outcomes.

P(A) = Number of Times ‘A’ OccursTotal Number of Possible OutcomesP(A)\ =\ \frac{\text{Number of Times `}A\text{' Occurs}}{\text{Total Number of Possible Outcomes}}P(A) = Total Number of Possible OutcomesNumber of Times ‘A’ Occurs

Unconditional probability is also known as marginal probability and measures the chance of an occurrence ignoring any knowledge gained from previous or external events. Since this probability ignores new information, it remains constant.

Example of Unconditional Probability

For example, let's examine a group of stocks. A stock can either be a winner, which earns a positive income, or a loser, which has a negative income. Out of five stocks, stock A and B are winners, while C, D, and E are losers. What is the unconditional probability of choosing a winning stock? Since two outcomes out of a possible five will produce a winner, the unconditional probability is 40% ( 2 / 5 ).