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Introducing Students to Classic Problems in Probability. Allan Rossman Department of Statistics Cal Poly – San Luis Obispo arossman@calpoly.edu. What’s my point?. Classic problems in probability Provide great opportunities for exploring, understanding concepts of randomness
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Introducing Students to Classic Problems in Probability Allan Rossman Department of Statistics Cal Poly – San Luis Obispo arossman@calpoly.edu NZAMT 2013
What’s my point? • Classic problems in probability • Provide great opportunities for exploring, understanding concepts of randomness • Lend themselves to interactive investigations • Can be presented at various mathematical levels • Illustrate mathematical as well as statistical ideas • Create pedagogical alternatives to rolling dice and flipping coins for their own sake • Are intellectually stimulating • Can be fun! NZAMT 2013
What are my goals for this workshop? • Acquaint you with some classic problems in probability • Demonstrate solutions to these problems • Using simulation • Using enumeration • Provide ideas for activities that you can use with your students • In variety of courses, levels NZAMT 2013
What concepts will be introduced? • Randomness • Probability • Simulation • Relative frequency • Permutations • Expected value • Decision making under uncertainty NZAMT 2013
What are these classic problems? • Problem of the points • Matching problem • Collector problem • Secretary problem NZAMT 2013
Problem of the points • Helped to motive the study of probability • Discussed in correspondence between Pascal and Fermat NZAMT 2013
Problem of the points • A simplified version: • Suppose that Heather and Tom each put in $5 to play a game • They flip a fair coin repeatedly • If 4 Heads occur before 4 Tails, Heather wins • If 4 Tails occur before 4 Heads, Tom wins NZAMT 2013
Problem of the points • Outcome: H H T H T (3 Heads, 2 Tails) • Then game is interrupted, cannot be completed! • How should the prize ($10) be divided? • What might you propose? NZAMT 2013
Problem of the points • My students’ answers • Game was not finished, so each takes $5 back • Heather won 3/5 of the flips, so she gets $6, Tom gets $4 • More mathematical approach • Divide prize proportionally to each player’s probability of winning if the game were continued NZAMT 2013
Problem of the points • How to calculate these probabilities? • Simulation • Enumeration • I’ll ask everyone to use a coin to simulate 5 repetitions of this random process • Remember that Heather wins with one more Head, but Tom needs two Tails to win • Estimate Heather’s probability of winning by proportion of times that she wins NZAMT 2013
Problem of the points • Enumeration analysis H: Heather wins TH: Heather wins TT: Tom wins • Are these equally likely, so Heather has 2/3 probability of winning? • No: H (prob .5), TH (prob .25), TT (prob .25) • Heather’s probability of winning: ¾ =.75 • So, Heather should take $7.50, Tom $2.50 NZAMT 2013
Problem of the points • Variation: What if they were playing to get 10 heads or tails and were interrupted after 9 heads and 8 tails? • Heather needs 1 more Head, Tom needs 2 more Tails • Same analysis, same answer! NZAMT 2013
Problem of the points • New variation: What if they were playing to 5 and had stopped after H H T H T? • More complicated enumeration: Heather wins with • H H (prob .25) • H T H (.125) • H T T H (.0625) • T H H (.125) • T H T H (.0625) • T T H H (.0625) • Heather has .6875 probability of winning • Heather should take $6.875 NZAMT 2013
Matching problem • Four mothers give birth to baby boys on the same night at the same hospital • As a very, Very, VERY sick joke (do not try this at home!), the hospital staff returns the babies to the mothers at random • How likely is it that everyone will get the right baby? Or nobody will? Or at least one will? • What is the average number that would get the right baby in the long run? NZAMT 2013
Matching problem • Simulate • Put baby’s name on each of four index cards • Shuffle cards thoroughly • Random distribute cards to four “mothers” • Repeat … • Repeat … • Repeat … • Approximate probabilities by proportions NZAMT 2013
Matching problem • Simulate • Turn to technology: Random Babies applet (www.rossmanchance.com/applets/) • Which is the most likely outcome? • How unlikely is getting 4 matches? • Is 3 very unlikely or impossible? • What’s the long-run average number of correct matches? • What happens as you conduct more repetitions? NZAMT 2013
Matching problem NZAMT 2013
Matching problem NZAMT 2013
Matching problem NZAMT 2013
Matching problem NZAMT 2013
Matching problem • Enumeration 1234 1243 1324 1342 1423 1432 2134 2143 2314 2341 2413 2431 3124 3142 3214 3241 3412 3421 4123 4132 4213 4231 4312 4321 • Count # of matches for each outcome NZAMT 2013
Matching problem • Enumeration 1234 1243 1324 1342 1423 1432 4 2 2 1 1 2 2134 2143 2314 2341 2413 2431 2 0 1 0 0 1 3124 3142 3214 3241 3412 3421 1 0 2 1 0 0 4123 4132 4213 4231 4312 4321 0 1 1 2 0 0 NZAMT 2013
Matching problem • Exact probabilities • 0 matches: 9/24 = .375 • 1 match: 8/24 ≈ .333 • 2 matches: 6/24 = .250 • 3 matches: 0 • 4 matches: 1/24 ≈ .042 • Expected value • 0(9/24) + 1(8/24) + 2(6/24) + 4(1/24) = 24/24 = 1 • Long-run average value NZAMT 2013
Collector problem • Each cereal box is equally likely to contain any one of 3 prizes • You want to collect the entire series of 3 prizes • Suppose that you buy boxes one at a time • What is the fewest that you might need to buy? • What is the most that you might need to buy? • How many boxes should you buy to have a 95% chance of success? • How many boxes do you “expect” to need (on average)? NZAMT 2013
Collector problem • What if there are k prizes? • Same questions as above • How likely are you to succeed if your strategy is to buy twice as many boxes as prizes? NZAMT 2013
Collector problem • Simulate! • Write each prize on an index card • Shuffle cards thoroughly • Select one card at random, note which prize • Repeat, until all prizes have been obtained • Note the number of selections needed • Repeat … • Repeat … • Estimate probability distribution (of number of boxes needed) by distribution of results NZAMT 2013
Collector problem • 3 prizes • 100,000 repetitions • Average: 5.483 boxes • Probability of success with 6 boxes: 0.742 • Boxes needed for ≥.95 probability: 11 NZAMT 2013
Collector problem • 4 prizes • 100,000 repetitions • Average: 8.326 boxes • Probability of success with 8 boxes: 0.625 • Boxes needed for ≥.95 probability: 16 NZAMT 2013
Collector problem • 10 prizes • 100,000 repetitions • Average: 29.322 boxes • Probability of success with 20 boxes: 0.214 • Boxes needed for ≥.95 probability: 51 NZAMT 2013
Secretary problem My all-time favorite probability/math problem! Your task is to hire a new employee, subject to these constraints: • You know how many candidates have applied (n) • The candidates arrive in random order • You interview candidates one at a time • You can rank candidates after interviewing them • But you have no prior sense of quality NZAMT 2013
Secretary problem More constraints: • After you have interviewed a candidate, you must decide immediately whether to hire • No follow-up interviews • No going back later • Your task is to choose the best! • Any other result: you’ve failed! NZAMT 2013
Secretary problem Predict the optimal probability of success when: • n = 3 • n = 12 • n = 500 • n = 4,484,451 (population of NZ) • n = 7,182,483,662 (world population) NZAMT 2013
Secretary problem • Enumeration for n = 1: A: 1 Probability of success = 1! NZAMT 2013
Secretary problem • Enumeration for n = 2: A: 12 B: 21 • Two strategies • Hire first candidate • Hire second candidate Probability of success = .5 NZAMT 2013
Secretary problem • Enumeration for n = 3: A: 123 B: 132 C: 213 D: 231 E: 312 F: 321 • Seems like probability of success = 1/3 • Can we do better? NZAMT 2013
Secretary problem • Key insight • We can learn from the first candidate • Optimal strategy • Let one go by • Then hire first candidate who is the best so far A: 123 B: 132 C: 213 D: 231E: 312 F: 321 NZAMT 2013
Secretary problem • Enumeration for n = 4: A: 1234 B: 1243 C: 1324 D: 1342 E: 1423 F: 1432 G: 2134 H: 2143 I: 2314 J: 2341 K: 2413 L: 2431 M: 3124 N: 3142 O: 3214 P: 3241 Q: 3412 R: 3421 S: 4123 T: 4132 U: 4213 V: 4231 W: 4312 X: 4321 • Same form for optimal strategy • But should we let 1 go by or let 2 go by? NZAMT 2013
Secretary problem Let 1 go by A: 1234 B: 1243 C: 1324 D: 1342 E: 1423 F: 1432 G: 2134 H: 2143 I: 2314 J: 2341 K: 2413 L: 2431 M: 3124 N: 3142 O: 3214 P: 3241 Q: 3412 R: 3421 S: 4123 T: 4132 U: 4213 V: 4231 W: 4312 X: 4321 • Probability of success = 11/24 ≈ .4583 NZAMT 2013
Secretary problem Let 2 go by A: 1234 B: 1243 C: 1324 D: 1342 E: 1423 F: 1432 G: 2134 H: 2143 I: 2314 J: 2341 K: 2413 L: 2431 M: 3124 N: 3142 O: 3214 P: 3241 Q: 3412 R: 3421 S: 4123 T: 4132 U: 4213 V: 4231 W: 4312 X: 4321 • Probability of success = 10/24 ≈ .4167 NZAMT 2013
Secretary problem • n = 4: • Optimal strategy • Let 1 go by, then hire first one who is best so far • Probability of success = 11/24 ≈ .4583 • Decreasing, but not as quickly as most expect NZAMT 2013
Secretary problem NZAMT 2013
Secretary problem NZAMT 2013
Secretary problem • Recall: • For large values of n: • And so: NZAMT 2013
Secretary problem • Recall: • Goal: choose r to maximize f(r) • Elementary calculus gives: • Optimal probability of success becomes: NZAMT 2013
Secretary problem Remarkable result: • As n gets infinitely large • Optimal strategy is to let ≈ first 1/e (about 37%) go by • Then hire first who is best so far • Optimal probability of success 1/e, about 37% NZAMT 2013
Secretary problem • Extensions • Hidden number game • Finding your soul-mate in life NZAMT 2013
Thanks! • arossman@calpoly.edu NZAMT 2013