math 341: probability first lecture - williams college · scribe: optional: taking turns...

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Introduction Mechanics Clicker Qs Math 341: Probability First Lecture Steven J Miller Williams College [email protected] http://www.williams.edu/go/math/sjmiller/ public html/341/ Bronfman Science Center Williams College, September 10, 2009 1

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Page 1: Math 341: Probability First Lecture - Williams College · Scribe: optional: taking turns summarizing lecture / takeaways. Creating HW problems: mix of ones you can solve and ones

Introduction Mechanics Clicker Qs

Math 341: ProbabilityFirst Lecture

Steven J MillerWilliams College

[email protected]://www.williams.edu/go/math/sjmiller/

public html/341/

Bronfman Science CenterWilliams College, September 10, 2009

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Page 2: Math 341: Probability First Lecture - Williams College · Scribe: optional: taking turns summarizing lecture / takeaways. Creating HW problems: mix of ones you can solve and ones

Introduction Mechanics Clicker Qs

Introduction andObjectives

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Page 3: Math 341: Probability First Lecture - Williams College · Scribe: optional: taking turns summarizing lecture / takeaways. Creating HW problems: mix of ones you can solve and ones

Introduction Mechanics Clicker Qs

Introduction / Objectives

Probability theory: model the real world, predict likelihoodof events.

One of the three most important quantitative classes(statistics, programming).

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Page 4: Math 341: Probability First Lecture - Williams College · Scribe: optional: taking turns summarizing lecture / takeaways. Creating HW problems: mix of ones you can solve and ones

Introduction Mechanics Clicker Qs

Introduction / Objectives

Probability theory: model the real world, predict likelihoodof events.

One of the three most important quantitative classes(statistics, programming).

ObjectivesModel problems and analyze model.Emphasize techniques / asking the right questions.Elegant solutions vs brute force (parameters in closedform versus numerical solutions).Looking at equations and getting a sense: log−5Method: p±pq

p+q±2pq .

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Page 5: Math 341: Probability First Lecture - Williams College · Scribe: optional: taking turns summarizing lecture / takeaways. Creating HW problems: mix of ones you can solve and ones

Introduction Mechanics Clicker Qs

Types of Problems

Biology: will a species survive?Physics / Chemistry / Number Theory: RandomMatrix Theory.Gambling: Double-plus-one.Economics: Stock market / economy.Finance: Monte Carlo integration.Cryptography: Markov Chain Monte Carlo.8 ever 9 never

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Page 6: Math 341: Probability First Lecture - Williams College · Scribe: optional: taking turns summarizing lecture / takeaways. Creating HW problems: mix of ones you can solve and ones

Introduction Mechanics Clicker Qs

Types of Problems

Biology: will a species survive?Physics / Chemistry / Number Theory: RandomMatrix Theory.Gambling: Double-plus-one.Economics: Stock market / economy.Finance: Monte Carlo integration.Cryptography: Markov Chain Monte Carlo.8 ever 9 never (bridge).

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Page 7: Math 341: Probability First Lecture - Williams College · Scribe: optional: taking turns summarizing lecture / takeaways. Creating HW problems: mix of ones you can solve and ones

Introduction Mechanics Clicker Qs

My (applied) experiences

Marketing: parameters for linear programming(SilverScreener).

Data integrity: detecting fraud with Benford’s Law(IRS, Iranian elections).

Sabermetrics: Pythagorean Won-Loss Theorem.

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Page 8: Math 341: Probability First Lecture - Williams College · Scribe: optional: taking turns summarizing lecture / takeaways. Creating HW problems: mix of ones you can solve and ones

Introduction Mechanics Clicker Qs

Course Mechanics

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Page 9: Math 341: Probability First Lecture - Williams College · Scribe: optional: taking turns summarizing lecture / takeaways. Creating HW problems: mix of ones you can solve and ones

Introduction Mechanics Clicker Qs

Material

Move at fast pace, responsible for preparing for class.Excellent book: phenomenal problems, detailedexplanations.Supplemental book: interesting tidbits (cards atbreak: not Mafia!).Will cover most of Chapters 1 through 4, somecombinatorics, generating functions and the CentralLimit Theorem (CLT), and topics TBD by class.Pre-reqs: mostly calculus and basic combinatorics /set theory, need some multivariable calculus for somecomputations, linear algebra helps interpret someresults, complex analysis for proof of the CLT.

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Page 10: Math 341: Probability First Lecture - Williams College · Scribe: optional: taking turns summarizing lecture / takeaways. Creating HW problems: mix of ones you can solve and ones

Introduction Mechanics Clicker Qs

Administrative

Grading

HW 20%, midterms 40%, final 40%.Will be 2 or 3 midterms, at least 1 or 2 take home,lowest dropped.Tests will always have at least one question ‘do 1 of2’.Project option: 10%, scale back rest.

Office hours / feedback

Regular TBD, weekly dinner (?), whenever I’m in myoffice (schedule online).Feedback: [email protected], password first 7Fibonacci numbers (11235813).

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Page 11: Math 341: Probability First Lecture - Williams College · Scribe: optional: taking turns summarizing lecture / takeaways. Creating HW problems: mix of ones you can solve and ones

Introduction Mechanics Clicker Qs

Office hour explanation

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Page 12: Math 341: Probability First Lecture - Williams College · Scribe: optional: taking turns summarizing lecture / takeaways. Creating HW problems: mix of ones you can solve and ones

Introduction Mechanics Clicker Qs

Other

Webpage: numerous handouts, additional commentseach day (mix of review and optional advancedmaterial).Clickers: see how well we can estimate probabilities,always anonymous.Probability Lifesaver: opportunity to help write a book,lots of worked examples.Scribe: optional: taking turns summarizing lecture /takeaways.Creating HW problems: mix of ones you can solveand ones you want to learn about.Gather and analyze some data set of interest.PREPARE FOR CLASS! Must do readings beforeeach class.

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Page 13: Math 341: Probability First Lecture - Williams College · Scribe: optional: taking turns summarizing lecture / takeaways. Creating HW problems: mix of ones you can solve and ones

Introduction Mechanics Clicker Qs

Clicker Problems

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Page 14: Math 341: Probability First Lecture - Williams College · Scribe: optional: taking turns summarizing lecture / takeaways. Creating HW problems: mix of ones you can solve and ones

Introduction Mechanics Clicker Qs

Birthday Problem I

Birthday ProblemHow large must N be for there to be at least a 50%probability that two of the N people share a birthday?

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Page 15: Math 341: Probability First Lecture - Williams College · Scribe: optional: taking turns summarizing lecture / takeaways. Creating HW problems: mix of ones you can solve and ones

Introduction Mechanics Clicker Qs

Birthday Problem I

Birthday ProblemHow large must N be for there to be at least a 50%probability that two of the N people share a birthday?

(A) 11 people(B) 22 people(C) 33 people(D) 44 people(E) 90 people(F) 180 people(G) 365 people(H) 500 people.

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Page 16: Math 341: Probability First Lecture - Williams College · Scribe: optional: taking turns summarizing lecture / takeaways. Creating HW problems: mix of ones you can solve and ones

Introduction Mechanics Clicker Qs

Birthday Problem I

Birthday ProblemHow large must N be for there to be at least a 50%probability that two of the N people share a birthday?

10 20 30 40 50n

0.2

0.4

0.6

0.8

1.0

Probability

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Page 17: Math 341: Probability First Lecture - Williams College · Scribe: optional: taking turns summarizing lecture / takeaways. Creating HW problems: mix of ones you can solve and ones

Introduction Mechanics Clicker Qs

Birthday Problem II

How large must N be for there to be at least a 50%probability that two of N Plutonians share a birthday?

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Page 18: Math 341: Probability First Lecture - Williams College · Scribe: optional: taking turns summarizing lecture / takeaways. Creating HW problems: mix of ones you can solve and ones

Introduction Mechanics Clicker Qs

Birthday Problem II

How large must N be for there to be at least a 50%probability that two of N Plutonians share a birthday?‘Recall’ one Plutonian year is about 248 Earth years (or90,520 days).

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Page 19: Math 341: Probability First Lecture - Williams College · Scribe: optional: taking turns summarizing lecture / takeaways. Creating HW problems: mix of ones you can solve and ones

Introduction Mechanics Clicker Qs

Birthday Problem II

How large must N be for there to be at least a 50%probability that two of N Plutonians share a birthday?‘Recall’ one Plutonian year is about 248 Earth years (or90,520 days).

(A) 110 people(B) 220 people(C) 330 people(D) 440 people(E) 1,000 people(F) 5,000 people(G) 10,000 people(H) 20,000 people(I) more than 30,000 people.

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Page 20: Math 341: Probability First Lecture - Williams College · Scribe: optional: taking turns summarizing lecture / takeaways. Creating HW problems: mix of ones you can solve and ones

Introduction Mechanics Clicker Qs

Birthday Problem II

How large must N be for there to be at least a 50%probability that two of N Plutonians share a birthday?‘Recall’ one Plutonian year is about 248 Earth years (or90,520 days).

200 400 600 800n

0.2

0.4

0.6

0.8

1.0

Probability

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Page 21: Math 341: Probability First Lecture - Williams College · Scribe: optional: taking turns summarizing lecture / takeaways. Creating HW problems: mix of ones you can solve and ones

Introduction Mechanics Clicker Qs

Voting: Democratic Primaries

During the Democratic primaries, Clinton and Obamareceived exactly the same number of votes in Syracuse,NY. How probable was this?

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Page 22: Math 341: Probability First Lecture - Williams College · Scribe: optional: taking turns summarizing lecture / takeaways. Creating HW problems: mix of ones you can solve and ones

Introduction Mechanics Clicker Qs

Voting: Democratic Primaries

During the Democratic primaries, Clinton and Obamareceived exactly the same number of votes in Syracuse,NY. How probable was this? (Note: they each received6001 votes.)

(A) 1 / 10(B) 1 / 100(C) 1 / 1,000(D) 1 / 10,000(E) 1 / 100,000(F) 1 / 1,000,000 (one in a million)(G) 1 / 1,000,000,000 (one in a billion).

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Page 23: Math 341: Probability First Lecture - Williams College · Scribe: optional: taking turns summarizing lecture / takeaways. Creating HW problems: mix of ones you can solve and ones

Introduction Mechanics Clicker Qs

Voting: Democratic Primaries (continued)

Syracuse University mathematics Professor Hyune-JuKim said the result was less than one in a million,according to the Syracuse Post-Standard, which quotedthe professor as saying, “It’s almost impossible.” Hercomments were reprinted widely, as the Associated Presspicked up the story. (Carl Bialik, WSJ, 2/12/08)

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Page 24: Math 341: Probability First Lecture - Williams College · Scribe: optional: taking turns summarizing lecture / takeaways. Creating HW problems: mix of ones you can solve and ones

Introduction Mechanics Clicker Qs

Voting: Democratic Primaries (continued)

Syracuse University mathematics Professor Hyune-JuKim said the result was less than one in a million,according to the Syracuse Post-Standard, which quotedthe professor as saying, “It’s almost impossible.” Hercomments were reprinted widely, as the Associated Presspicked up the story. (Carl Bialik, WSJ, 2/12/08)

Far greater than 1/137! What’s going on?

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Page 25: Math 341: Probability First Lecture - Williams College · Scribe: optional: taking turns summarizing lecture / takeaways. Creating HW problems: mix of ones you can solve and ones

Introduction Mechanics Clicker Qs

Voting: Democratic Primaries (continued)

Syracuse University mathematics Professor Hyune-JuKim said the result was less than one in a million,according to the Syracuse Post-Standard, which quotedthe professor as saying, “It’s almost impossible.” Hercomments were reprinted widely, as the Associated Presspicked up the story. (Carl Bialik, WSJ, 2/12/08)

Far greater than 1/137! What’s going on?

Prof. Kim’s calculation ... was based on the assumptionthat Syracuse voters were likely to vote in equalproportions to the state as a whole, which went for Ms.Clinton, its junior senator, 57%-40%. .... Prof. Kim saidshe had little time to make the calculation, so she madethe questionable assumption ... for simplicity.

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