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Section 9.1 Great Expectations Deciding How to Weigh the Unknown Future

Section 9.1 Great Expectations Deciding How to Weigh the Unknown Future. Chance favors only the prepared mind. Louis Pasteur. Question of the Day. If your bicycle is worth $1000, does it make sense to buy theft insurance that costs $50 per year?. Expected Value.

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Section 9.1 Great Expectations Deciding How to Weigh the Unknown Future

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  1. Section 9.1Great ExpectationsDeciding How to Weigh the Unknown Future Chance favors only the prepared mind. Louis Pasteur

  2. Question of the Day If your bicycle is worth $1000, does it make sense to buy theft insurance that costs $50 per year?

  3. Expected Value Expected value the average net gain or loss that we would expect per game if we played the game many times.

  4. Expected Value Computing Expected Value: To compute the expected value, we multiply the value of each outcome with its probability of occurring and then add up all those products.

  5. Expected Value A game is called a fair game if the expected value equals zero.

  6. Paradox A paradox presents a situation that has two possible interpretations or resolutions. Each view appears irrefutable, and yet the views are diametrically opposed to each other.

  7. Newcomb’s Paradox

  8. Section 9.2RiskDeciding Personal and Public Policy The moral: Beware of unintended consequences.

  9. Question of the Day An HIV test is 95% accurate for infected people. Suppose your roommate’s test result is positive. What are the chances your roommate has HIV?

  10. Goal When facing issues, we want to take steps to help us make informed decisions.

  11. Risk How do we measure risk?

  12. Consider Unintended Consequences

  13. Section 9.3Money MattersDeciding Between Faring Well and Welfare Lack of money is the root of all evil. Mark Twain

  14. Question of the Day Adam and Eve invest one penny in a bank account paying 3% compounded annually. How much money will the account hold after 1000 years: $10,000? $100,000? $1 million? $1 billion?

  15. A Compounding Pattern

  16. Section 9.4Peril at the PollsDeciding Who Actually Wins an Election … Democracy is the worst form of government except all those others that have been tried from time to time. Winston Churchill

  17. Question of the Day How do you pick the winner of a democratic election?

  18. An Election Conundrum

  19. Simple Voting Methods Plurality Voting Each voter votes for one person, and the candidate with the most votes wins.

  20. Simple Voting Methods Vote-for-Two Each voter must vote for two different candidates and the candidate with the most votes wins.

  21. Simple Voting Methods Borda Count Each voter ranks all the candidates: 1, 2, 3, and so on. The highest ranking is 1. The rankings are then tallied for each candidate, and the candidate with the lowest total wins.

  22. Condorcet’s Paradox The cumulative ranking of the group as a whole may not be transitive – that is, the ranking may have a circle of preferences.

  23. Arrow’s Election Disaster Theorem

  24. Section 9.5Cutting Cake for Greedy PeopleDeciding How to Slice Up Scarce Resources Choose a convenient representation of an issue.

  25. Question of the Day Can you always cut a cake so that everyone gets his or her favorite piece?

  26. Cake-Cutting Question Given a cake and three people, is there a method of cutting the cake equitably?

  27. Greedy Division Question Given a cake and three people, is there a method for cutting cake into three pieces so that each person gets the piece that he or she believes has the greatest value? In other words, can the cake be divided into three pieces so that, of the resulting slices, everyone gets their favorite piece?

  28. Greedy Division Theorem Suppose three preference diagrams are superimposed. Then there will be a point where the three people have indicated that they all prefer different pieces.

  29. Four or More People What happens if we want to divide a cake among four people?

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