Unconditional Probability - Explained
What is Unconditional Probability?
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What is Unconditional Probability?
An unconditional probability is a probability theory that holds that an event is likely going to occur whether or not other events occur. In this theory, the chance of the occurrence of an event is not dependent on other events. External circumstances have no effect on the outcome of an event using the unconditional probability. Hence, there is probability for the event to have a particular result regardless of other conditions or forces present.
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How is Unconditional Probability Used?
Unlike conditional probability in which an event is likely to occur only if another event occurs, events under unconditional probability form no dependence on the occurrence of other events. Also, the outcomes of events under unconditional probability can be independent of other factors or possible outcomes present. Another name for unconditional probability is marginal probability, this theory gives no regard to other events present or other likely outcomes. Rather, an event can happen and outcome be achieved irrespective of whether other options are present or otherwise. Also, the outcomes of previous events do not determine the outcome of the present event, they run independent of one another.
Example of Unconditional Probability
The common example of unconditional probability is the probability that it will snow in northwestern Wyoming regardless of the fact that previous data and other events have contrary reports. This is an unconditional probability which maintains that the snow is likely to happen independent of historical weather forecasts or available data. Unconditional probability can also be used for a group of stocks, in this case, a stock is like to give a specific result regardless of the presence or performance of other stocks in that group. If there are five stocks in a portfolio for example, one of them might outperform other stocks irrespective of market forces or the poor performance of other stocks.
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