Assignment Details 2244 BQOM 2512 SEC1280 ADVANCED DECISION TECHNOLOGY OWILOT TO Light Mo So, it's come...

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Assignment Details 2244 BQOM 2512 SEC1280 ADVANCED DECISION TECHNOLOGY OWILOT TO Light Mo "So, it's come down to this," thought Roger Mellichamp as he looked around at the empty Styrofoam coffee cups and papers littering his office. When he accepted the job of campaign manager for his long-time friend's run for the White House, he knew there would be long hours, lots of traveling, and constant media pressure. But the thing he most wanted to avoid was a close race with a final showdown just before the election. Roger knew that making decisions under those circumstances would be agonizing because the success of the campaign and, in many ways, the future of the country would hinge on those very decisions. Unfortunately, that's just where things stand. With only two weeks before the U.S. presidential election, Roger's friend and the incumbent president are running neck-and-neck in the polls. So, Roger's plans for the final two weeks of the campaign will be critical, and he wants to make sure he uses the candidate's time and the campaign's remaining money in the most effective way. Although the outcome of the election has been pretty much decided in most states, the electoral votes from the states of Florida, Georgia, California, Texas, Illinois, New York, Virginia, and Michigan are still up for grabs by either candidate. Roger knows they must win as many of these states as possible if his friend is to become the next president. Several weeks ago, it became evident that the race was going to be close. So, Roger hired a statistical consultant to estimate the percentage of votes the campaign will receive in each of the states based on the amount of money the campaign spends and the number of times the candidate visits each state during the final two weeks before the election. The results of the consultant's analysis provided the following function: Percentage of votes state k =1 -EXP(-aVk -bDk) where: Vk: the number of times the candidate visits state k in the last two weeks of the campaign, Dk: the dollars (in $1,000,000s) the campaign spends on advertising in state k in the last two weeks of the campaign The following table summarizes the consultant's estimates of the parameters a and b for each state, along with the number of electoral votes at stake in each state: Assignment Details 2244 BQOM 2512 SEC1280 ADVANCED DECISION TECHNOLOGY OWILOT TO Light Mo "So, it's come down to this," thought Roger Mellichamp as he looked around at the empty Styrofoam coffee cups and papers littering his office. When he accepted the job of campaign manager for his long-time friend's run for the White House, he knew there would be long hours, lots of traveling, and constant media pressure. But the thing he most wanted to avoid was a close race with a final showdown just before the election. Roger knew that making decisions under those circumstances would be agonizing because the success of the campaign and, in many ways, the future of the country would hinge on those very decisions. Unfortunately, that's just where things stand. With only two weeks before the U.S. presidential election, Roger's friend and the incumbent president are running neck-and-neck in the polls. So, Roger's plans for the final two weeks of the campaign will be critical, and he wants to make sure he uses the candidate's time and the campaign's remaining money in the most effective way. Although the outcome of the election has been pretty much decided in most states, the electoral votes from the states of Florida, Georgia, California, Texas, Illinois, New York, Virginia, and Michigan are still up for grabs by either candidate. Roger knows they must win as many of these states as possible if his friend is to become the next president. Several weeks ago, it became evident that the race was going to be close. So, Roger hired a statistical consultant to estimate the percentage of votes the campaign will receive in each of the states based on the amount of money the campaign spends and the number of times the candidate visits each state during the final two weeks before the election. The results of the consultant's analysis provided the following function: Percentage of votes state k =1 -EXP(-aVk -bDk) where: Vk: the number of times the candidate visits state k in the last two weeks of the campaign, Dk: the dollars (in $1,000,000s) the campaign spends on advertising in state k in the last two weeks of the campaign The following table summarizes the consultant's estimates of the parameters a and b for each state, along with the number of electoral votes at stake in each state: