Stat 35b: Introduction to Probability with Applications to Poker Outline for the day: 1.Hand in hw1! Get hw2. 2.Combos, permutations, and A  vs 2  after.

Slides:



Advertisements
Similar presentations
Problem Set 3 20.)A six-sided die (whose faces are numbered 1 through 6, as usual) is known to be counterfeit: The probability of rolling any even number.
Advertisements

1 Some more probability Samuel Marateck © Another way of calculating card probabilities. What’s the probability of choosing a hand of cards with.
Probability Sample Space Diagrams.
Multiplication Rules for Probability Independent Events Two events are independent if the fact that A occurs does not affect the probability of B occuring.
Dependent and Independent Events. If you have events that occur together or in a row, they are considered to be compound events (involve two or more separate.
CONDITIONAL PROBABILITY and INDEPENDENCE In many experiments we have partial information about the outcome, when we use this info the sample space becomes.
Section 5.2 The Addition Rule and Complements
Statistics Chapter 3: Probability.
Stat 35b: Introduction to Probability with Applications to Poker Outline for the day: 1.Ly vs Negreanu. 2.Flush draws and straight draws 3.Project B teams.
Statistical Reasoning for everyday life Intro to Probability and Statistics Mr. Spering – Room 113.
Stat 35b: Introduction to Probability with Applications to Poker Outline for the day: 1.Straight draws. 2.HW2 clarification. 3.Greenstein vs. Farha AA.
Stat 35b: Introduction to Probability with Applications to Poker Outline for the day: 1.Hand in hw4. 2.Review list 3.Tournament 4.Sample problems * Final.
Stat 35b: Introduction to Probability with Applications to Poker Outline for the day: 0. Collect hw2, return hw1, give out hw3. 1.Project A competition.
Stat 35b: Introduction to Probability with Applications to Poker Outline for the day: 1.Midterm. 2.Review of Bernoulli and binomial random variables. 3.Geometric.
Stat 35: Introduction to Probability with Applications to Poker Outline for the day: 1.Addiction 2.Syllabus, etc. 3. Wasicka/Gold/Binger Example 4.Meaning.
Copyright © Ed2Net Learning Inc.1. 2 Warm Up Use the Counting principle to find the total number of outcomes in each situation 1. Choosing a car from.
Stat 35b: Introduction to Probability with Applications to Poker Outline for the day: 1.Collect Hw4. 2.Review list. 3.Answers to hw4. 4.Project B tournament.
AP Statistics Chapter 6 Notes. Probability Terms Random: Individual outcomes are uncertain, but there is a predictable distribution of outcomes in the.
Dependent and Independent Events. Events are said to be independent if the occurrence of one event has no effect on the occurrence of another. For example,
Stat 35b: Introduction to Probability with Applications to Poker Outline for the day, Tue 3/13/12: 1.Collect Hw WSOP main event. 3.Review list.
Stat 35b: Introduction to Probability with Applications to Poker Outline for the day: 1.hw, terms, etc. 2.WSOP example 3. permutations, and combinations.
Stat 35b: Introduction to Probability with Applications to Poker Outline for the day: 1.Addiction 2.Syllabus, etc. 3. Wasicka/Gold/Binger Example 4.Meaning.
Stat 35b: Introduction to Probability with Applications to Poker Outline for the day: 1.HW3 2.Project B teams 3.Gold vs. Helmuth 4.Farha vs. Gold 5.Flush.
Stat 35b: Introduction to Probability with Applications to Poker Outline for the day: 1.Deal-making and expected value 2.Odds ratios, revisited 3.Variance.
Natural Language Processing Giuseppe Attardi Introduction to Probability IP notice: some slides from: Dan Jurafsky, Jim Martin, Sandiway Fong, Dan Klein.
Stat 35b: Introduction to Probability with Applications to Poker Outline for the day: 1. Review list 2.Bayes’ Rule example 3.CLT example 4.Other examples.
Stat 35b: Introduction to Probability with Applications to Poker Outline for the day: 1.Expected value and pot odds, continued 2.Violette/Elezra example.
Conditional Probability and the Multiplication Rule NOTES Coach Bridges.
Multiplication Rule Statistics B Mr. Evans. Addition vs. Multiplication Rule The addition rule helped us solve problems when we performed one task and.
Stat 13, Thu 4/19/ Hand in HW2! 1. Resistance. 2. n-1 in sample sd formula, and parameters and statistics. 3. Probability basic terminology. 4. Probability.
Probability. Randomness When we produce data by randomized procedures, the laws of probability answer the question, “What would happen if we did this.
Stat 35b: Introduction to Probability with Applications to Poker Outline for the day: 1.Odds ratios revisited. 2.Gold/Hellmuth. 3.Deal making. 4.Variance.
Stat 35b: Introduction to Probability with Applications to Poker Outline for the day: 1.Hw, terms, etc. 2.Ly vs. Negreanu (flush draw) example 3. Permutations.
Stat 35b: Introduction to Probability with Applications to Poker Outline for the day: 1.Tournaments 2.Review list 3.Random walk and other examples 4.Evaluations.
Probability. Probability of an Event A measure of the likelihood that an event will occur. Example: What is the probability of selecting a heart from.
Warm Up: Quick Write Which is more likely, flipping exactly 3 heads in 10 coin flips or flipping exactly 4 heads in 5 coin flips ?
16.2 Probability of Events Occurring Together
(Day 14 was review. Day 15 was the midterm.) Stat 35b: Introduction to Probability with Applications to Poker Outline for the day: 1.Return and review.
Outline: 1) Odds ratios, continued. 2) Expected value revisited, Harrington’s strategy 3) Pot odds 4) Examples.
Stat 35b: Introduction to Probability with Applications to Poker Outline for the day: 1. Combos, permutations, and A  vs 2  after first ace 2.Conditional.
Stat 35b: Introduction to Probability with Applications to Poker Outline for the day: 1.Hw, terms, etc. 2.Ly vs. Negreanu (flush draw) example 3. Axioms.
Stat 35b: Introduction to Probability with Applications to Poker Outline for the day: 1.Expected value. 2.Heads up with AA. 3.Heads up with Gus vs.
Chance We will base on the frequency theory to study chances (or probability).
Stat 35b: Introduction to Probability with Applications to Poker Outline for the day: 1.Review List 2.Review of Discrete variables 3.Nguyen / Szenkuti.
1.A true-false quiz has five questions. Use the Fundamental Counting Principle to find the total number of ways that you can answer the quiz. 2. You spin.
Stat 35b: Introduction to Probability with Applications to Poker Outline for the day: 1.Hw, terms, etc. 2.Ly vs. Negreanu (flush draw) example 3. Permutations.
Stat 35b: Introduction to Probability with Applications to Poker Outline for the day: 1.Odds ratio example again. 2.Random variables. 3.cdf, pmf, and density,
Introduction to probability (3) Definition: - The probability of an event A is the sum of the weights of all sample point in A therefore If A1,A2,…..,An.
World Series of Poker Main Event 2005, Day 1, from cardplayer.com: *Date / Time:* :23:00 With the board showing 10  9  5  Q , Chris "Jesus"
Stat 35b: Introduction to Probability with Applications to Poker
Stat 35b: Introduction to Probability with Applications to Poker
Stat 35b: Introduction to Probability with Applications to Poker
Stat 35b: Introduction to Probability with Applications to Poker
Stat 35b: Introduction to Probability with Applications to Poker
Probability ·  fraction that tells how likely something is to happen ·   the relative frequency that an event will occur.
LEARNING GOAL The student will understand how to calculate the probability of an event.
Stat 35b: Introduction to Probability with Applications to Poker
Multiplication Rule and Conditional Probability
Stat 35b: Introduction to Probability with Applications to Poker
Stat 35b: Introduction to Probability with Applications to Poker
Stat 35b: Introduction to Probability with Applications to Poker
Stat 35b: Introduction to Probability with Applications to Poker
I can find probabilities of compound events.
Chapter 3.1 Probability Students will learn several ways to model situations involving probability, such as tree diagrams and area models. They will.
Probability. ·. fraction that tells. how likely something. `
Stat 35: Introduction to Probability with Applications to Poker
Stat 35b: Introduction to Probability with Applications to Poker
Stat 35b: Introduction to Probability with Applications to Poker
Stat 35b: Introduction to Probability with Applications to Poker
Stat 35b: Introduction to Probability with Applications to Poker
Presentation transcript:

Stat 35b: Introduction to Probability with Applications to Poker Outline for the day: 1.Hand in hw1! Get hw2. 2.Combos, permutations, and A  vs 2  after first ace 3.Conditional prob., independence, & multiplication rule 4.Independence and dependence examples 5.More counting problems: straight draw example season 1, episode 4, part 3, 6:36.   u 

1.HAND IN HW1! 2.Deal til first ace appears. Let X = the next card after the ace. P(X = A  )? P(X = 2  )? (a) How many permutations of the 52 cards are there? 52! (b) How many of these perms. have A  right after the 1st ace? (i) How many perms of the other 51 cards are there? 51! (ii) For each of these, imagine putting the A  right after the 1st ace. 1:1 correspondence between permutations of the other 51 cards & permutations of 52 cards such that A  is right after 1st ace. So, the answer to question (b) is 51!. Answer to the overall question is 51! / 52! = 1/52. Obviously, same goes for 2 .

3. Conditional Probability and Independence P(A & B) is often written “P(AB)”. “P(A U B)” means P(A or B [or both]). Conditional Probability: P(A given B) [written“P(A|B)”] = P(AB) / P(B). Independent: A and B are “independent” if P(A|B) = P(A). Fact (multiplication rule for independent events): If A and B are independent, then P(AB) = P(A) x P(B) Fact (general multiplication rule): P(AB) = P(A) P(B|A) P(ABC…) = P(A) x P(B|A) x P(C|A&B) …

4. Independence and Dependence Examples Independence: P(A | B) = P(A) [and P(B|A) = P(B)]. So, when independent, P(A&B) = P(A)P(B|A) = P(A)P(B). Reasonable to assume the following are independent: a) Outcomes on different rolls of a die. b) Outcomes on different flips of a coin. c) Outcomes on different spins of a spinner. d) Outcomes on different poker hands. e) Outcomes when sampling from a large population. Ex: P(you get AA on 1st hand and I get AA on 2nd hand) = P(you get AA on 1st) x P(I get AA on 2nd) = 1/221 x 1/221 = 1/4641. P(you get AA on 1st hand and I get AA on 1st hand) = P(you get AA) x P(I get AA | you have AA) = 1/221 x 1/(50 choose 2) = 1/221 x 1/1225 = 1/

Example: High Stakes Poker, 1/8/07: season 1, episode 4, part 3, 6:36. Greenstein folds, Todd Brunson folds, Harman folds. Elezra calls $600, Farha (K  J  ) raises to $2600, Sheikhan folds. Negreanu calls, Elezra calls. Pot is $8,800. Flop: 6  10  8 . Negreanu bets $5000. Elezra raises to $ Farha folds. Negreanu thinks for 2 minutes….. then goes all-in for another $96,000. Elezra: 8  6 . (Elezra calls. Pot is $214,800.) Negreanu: A u 10  At this point, the odds on tv show 73% for Elezra and 25% for Negreanu. They “run it twice”. First: 2  4 . Second time? A  8 u ! P(Negreanu hits an A or 10 on turn & still loses)?

Given both their hands, and the flop, and the first “run”, what is P(Negreanu hits an A or 10 on the turn & loses)? Since he can’t lose if he hits a 10 on the turn, it’s: P(A on turn & Negreanu loses) = P(A on turn) x P(Negreanu loses | A on the turn) = 3/43 x 4/42 = 0.66% (1 in 150.5) Note: this is very different from: P(A or 10 on turn) x P(Negreanu loses), which would be about 5/43 x 73% = 8.49% (1 in 12)

5. More counting problems: straight draw example World Series of Poker Main Event 2005, Day 1, from cardplayer.com: With the board showing 10  9  5  Q , Chris "Jesus" Ferguson moves all in. Kalee Tan calls. Ferguson shows Q-Q for a set of queens, and Tan flips up J-8 for a queen high straight. Ferguson needs the board to pair in order to stay alive. The river is the 8 , no help to Ferguson, and he is eliminated on Day 1. Kalee Tan drags the pot with uncontrollably shaky hands as Ferguson heads to the rail. Q: What is the probability of flopping an open- end straight draw, given you have J-8? What about J-9 or J-T?

A: For J-8, you need the flop to be KQT or T9x or 976 or 765. Consider the case where x is T or 9 separately (x ≠ Q or 7!). So the probability is: P( KQT or TT9 or T99 or T9x or 976 or 765 ) = 4 x 4 x 4 + C(4,2) x 4 + C(4,2) x x 4 x x 4 x x 4 x 4 C(50,3) = 4.0%, or 1 in 25. A: For J-9, you need KT7 or T8x or QTx or 876, so it’s P( KT7 or TT8 or T88 or QQT or QTT or T8x or QTx or 876) = 64 + [C(4,2) x 4] x 4 + [4 x 4 x 34] x C(50,3) = 6.7%, or about 1 in 15.

A: For J-T, you need: KQx, Q9x, 98x, AQ8, K97, KKQ, KQQ, QQ9, Q99, 998, or 988. So the probability is: 3 x [4 x 4 x 34] + 2 x [4 x 4 x 4] + 6 x [C(4,2) x 4] C(50,3) = 9.71%, or about 1 in 10.