While some may argue that it is not an issue that voter turnout statistics are low in the United States, both mathematical and theoretical reasoning would suggest that it is better to have as many people vote in an election as possible. Daniel Steven Roberts’s of the University of Tennessee states, “In theory, democracy functions best when more people participate...Without a fully representative electorate, there is little hope that the views of all citizens will be expressed or taken seriously. A democracy in which the views of all citizens are not conveyed cannot seriously be said to be a healthy democracy.” [6, p. 23-24] Political leaders are supposed to serve as representatives of the citizens of the United States, so if citizens want a
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Marquis de Condorcet’s jury theorem can be applied to the voting process. This theorem supposes a decision is being made between two choices, one given the value “+” and the other valued as “-” and one of the two choices is correct, even though it is unknown which one it is. The decision in this case is put to a vote, and each individual in a group, represented by n, gets a single vote, represented as xi in this scenario. Each vote for the “+” choice is equal to 1, and each vote for the “-” choice is -1. The group’s decision is based on whether the sum of the votes represented by the equation Sn = ∑ni=1 xi is positive or negative. The theorem then states, “If the individual votes (xi, i=1,...,n) are independent of one another, and each voter makes the correct decision with probability p > ½, then as n [approaches infinity], the probability of the group coming to a correct decision by majority vote tends to 1” [7, p. 1]. This suggests that with a greater population voting, there is a higher likelihood of the correct choice being made in an election. Roberts adds to the support of the jury theorem by stating, “Doing the math according to Condorcet, a majority of only 51 of the 100 will have a 52% chance of being correct. Condorcet said that if the majority increases to 55 out of the 100, then the probability that the majority has made the correct choice increases to 60%. In short, …show more content…
Columbia University’s Andrew Gelman, along with statistician Nate Silver and Aaron Edlin of the University of California Berkeley, sought out to calculate the probability that a vote would be decisive in an election. This probability is based on the probability that an individual’s state is necessary for a win in the Electoral College multiplied by the probability that the vote is tied. After using polls for the then-upcoming 2008 presidential election, 10,000 computer simulations for the election in a 10,000 by 51 matrix, and multiplying the numerical vote margin by the voter turnout in each individual state, state-by-state probabilities of a vote being decisive in a state could be calculated. The states with the greatest probability of a vote being crucial were New Mexico, New Hampshire, Virginia, and Colorado, and at best, the probability of the vote being decisive would be approximately 1 in 10 million, with the probability in bigger states, such as New York, California, and Texas, being closer to 1 in 1 Billion. Combining every state and Washington D.C., there is approximately a 1 in 60 million chance that a randomly selected vote would be decisive.
Marquis de Condorcet’s jury theorem can be applied to the voting process. This theorem supposes a decision is being made between two choices, one given the value “+” and the other valued as “-” and one of the two choices is correct, even though it is unknown which one it is. The decision in this case is put to a vote, and each individual in a group, represented by n, gets a single vote, represented as xi in this scenario. Each vote for the “+” choice is equal to 1, and each vote for the “-” choice is -1. The group’s decision is based on whether the sum of the votes represented by the equation Sn = ∑ni=1 xi is positive or negative. The theorem then states, “If the individual votes (xi, i=1,...,n) are independent of one another, and each voter makes the correct decision with probability p > ½, then as n [approaches infinity], the probability of the group coming to a correct decision by majority vote tends to 1” [7, p. 1]. This suggests that with a greater population voting, there is a higher likelihood of the correct choice being made in an election. Roberts adds to the support of the jury theorem by stating, “Doing the math according to Condorcet, a majority of only 51 of the 100 will have a 52% chance of being correct. Condorcet said that if the majority increases to 55 out of the 100, then the probability that the majority has made the correct choice increases to 60%. In short, …show more content…
Columbia University’s Andrew Gelman, along with statistician Nate Silver and Aaron Edlin of the University of California Berkeley, sought out to calculate the probability that a vote would be decisive in an election. This probability is based on the probability that an individual’s state is necessary for a win in the Electoral College multiplied by the probability that the vote is tied. After using polls for the then-upcoming 2008 presidential election, 10,000 computer simulations for the election in a 10,000 by 51 matrix, and multiplying the numerical vote margin by the voter turnout in each individual state, state-by-state probabilities of a vote being decisive in a state could be calculated. The states with the greatest probability of a vote being crucial were New Mexico, New Hampshire, Virginia, and Colorado, and at best, the probability of the vote being decisive would be approximately 1 in 10 million, with the probability in bigger states, such as New York, California, and Texas, being closer to 1 in 1 Billion. Combining every state and Washington D.C., there is approximately a 1 in 60 million chance that a randomly selected vote would be decisive.