Conditional probability refers to the probability of one event occurring with some relationship to one or more other events (Evans, Handley & Over, 2013). For instance, in politics, the chance re-election for any seat is dependent upon factors such as the success of the various forms of campaign, the voting preferences of the voters and the possibility of the opponent making blunders in their campaign strategies. The success of President Obama’s re-election is an example of conditional probability given that it was dependent on the strength of his television and online campaign amid intense competition, the preference of the voters, the strength of the votes from the electoral college and that of not having to fight for his party’s nomination.
President Obama’s campaign strategies that heavily relied on the internet were significant in swaying the voters into re-electing him despite his unaccomplished projects in the previous term. In addition, he gained from the outpouring votes from minorities, young adults and lower income families given that most of them could identify with his established policies and promises. The strength of not having to fight for Democratic Party nomination was an event that contributed to the re-election. For the Republican Party, there was intense competition to determine who would clinch the official opponent positions and is turned out, the winner was not popular among the Republican voters as well as those in the electoral college.
The events leading to the success of the re-election were mutually exclusive given that they could not take place at the same time (Evans, Handley & Over, 2013). For instance, the Republican Party had to first conduct its election to determine the official opponent before campaigns would begin officially. Voting by the electoral college could not have happened until elections were over. In this event, probability rule one applied.
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Evans, J. S. B., Handley, S. J., & Over, D. E. (2013). Conditionals and conditional probability. Journal of Experimental Psychology: Learning, Memory, and Cognition, 29(2), 321.