Math 55: Discrete Mathematics
|
|
|
- Thomas Hamilton
- 10 years ago
- Views:
Transcription
1 Math 55: Discrete Mathematics UC Berkeley, Fall 2011 Homework # 7, due Wedneday, March 14 Happy Pi Day! (If any errors are spotted, please them to morrison at math dot berkeley dot edu A croissant shop has plain croissants, cherry croissants, chocolate croissants, almond croissants, apple croissants, and broccoli croissants. How many ways are there to choose (a a dozen croissants? Solution. This is equivalent to putting 12 indistinguishable objects into distinguishable boxes. (The boxes are the types of croissants, and putting objects into them corresponds to choosing that many of that type. The number of ways of doing this is = (b three dozen croissants? Solution. Similar to part (a, this is equivalent to putting 3 indistinguishable objects into distinguishable boxes. The number of ways of doing this is = 749, (c two dozen croissants with at least two of each kind? 1
2 Solution. We may consider the first dozen croissants already picked out (two of each of the six kinds. Thus the number is the number of ways of choosing the remaining dozen, which by part (a is 188. (d two dozen croissants with no more than two broccoli croissants? Solution. We will add up three cases: no broccoli croissants, exactly one broccoli croissant, and exactly two broccoli croissants. These numbers are = 20, = 17, = 14, (The first is choosing 24 croissants from the 5 non-brocolli types; the second is choosing just 23, since we already have one broccoli; the third is choosing just 22, since we already have two broccolis. Adding up, we have ways total. 20, , , 950 = 52, 975 (e two dozen croissants with at least five chocolate croissants and at least three almond croissants? Solution. We have already chosen the first eight, so we need only choose the remaining sixteen. There are = 20, ways to do this. (f two dozen croissants with at least one plain croissant, at least two cherry croissants, at least three chocolate croissants, at least one almond croissants, at least two apple croissants, and no more than three broccoli croissants? 2
3 Solution. We have already chosen the first nine croissants, so we need merely count how many ways there are to choose the last fifteen, without choosing more than three broccoli croissants. Similar to part (c, this is the sum of = 3, = 3, = 2, = 1, These add to 3, , , , 820 = 11, 13 so there are 11, 13 ways of choosing How many ways are there to distribute 12 indistinguishable balls into distinguishable boxes? Solution. There are =, ways How many strings with five or more characters can be formed from the letters in SEERESS? Solution. We ll count up how many can be formed with seven characters, with six characters, and with five characters, then add them up. For length seven, we are putting {1, 2,..., 7} into the three boxes S, E, and R, with S receiving three numbers, E receiving three numbers, and R receiving one number. (For instance, if S gets 1, 2, 7, E gets 3
4 4, 5, and R gets 3, this corresponds to the anagram SSREEES. There are 7! 3! 3! 1! = 140 ways to do this. For length six, we have several cases. If we left out an R, we are putting {1,..., } into two distinguishable boxes, each of which gets three numbers; there are! 3! 3! = 20 ways to do this. If we left out an S, we are putting {1,..., } into three boxes which get three, two, and one! objects, respectively; there are 3! 2! 1! = 0 ways to do this. Leaving out an E symmetrically gives 0. Hence there are = 140 strings of length six. For length five, we once again have several cases: 5! Leave out an S and an R: we get an R: also 10. 3! 2! = 10. Leave out an E and Leave out two S s: we get 5! 3! 1! 1! = 20. Leave out two E s: also 20. Leave out an S and an E: we get 5! 2! 2! 1! = 30. This gives a total of = 90 strings of length five. All told, we get that = 310 strings with five or more characters can be formed from the letters in SEERESS In bridge, the 52 cards of a standard deck are dealt to four players. How many different ways are there to deal bridge hands to four players? Solution. This is equivalent to putting 52 distinguishable objects into 4 distinguishable boxes, with each box getting 13 objects. There are ways to do this. 52! ! 13! 13! 13! 4
5 .5.50 How many ways are there to distribute five distinguishable objects into three indistinguishable boxes? Solution. Using Stirling numbers, the answer is 3 S(5, j = S(5, 1 + S(5, 2 + S(5, 3. j=1 Let s compute these out. S(5, 1 = ( 1 i (1 i 5 1! i i=0 1 = 1 5 = 1. 0 S(5, 2 = ( 2 ( 1 i 2! i i=0 = 1 ( = 1 ( = (2 i S(5, 3 = ( 3 ( 1 i 3! i i=0 = 1 ( (3 i = 1 ( = Adding these up gives a total of How many terms are there in the expansion of (x + y + z 100? Solution. The number of terms in the expansion is the number of ways of writing x a y b z c, where a + b + c = 100 and a, b, c are nonnegative 5
6 integers. This is the number of ways of putting 100 indistinguishable balls into three distinguishable boxes. There are = ways to do this What is the probability that a five-card poker hand contains exactly one ace? Solution. There are four possibilities for the ace, and then we must choose 4 cards from the 48 non-ace cards. This gives us five-card hands with exactly one ace. Dividing by the total number of hands, which is 52 5, we find 4 (48 4 ( , 5 so the probability that a five-card poker hand contains exactly one ace is about What is the probability that a fair die never comes up an even number when it is rolled six times? Solution. The probability that any given die roll comes up odd is 1/2. Since the rolls are independent, the probability it comes up odd all six times is 1/2 = 1/4. This is the probability that a fair die never comes up an even number when it is rolled six times Find the probability of selecting none of the correct six integers in a lottery, where the order in which these integers are selected does not matter, from the positive numbers not exceeding (a 40. (b 48. (c 5.
7 (d 4. Solution. For 40, the number of ways of selecting all wrong numbers is the number of ways of selecting six numbers from the 34 incorrect numbers. There are ( 34 ways to do this. Since there are 40 ways to choose numbers in total, the probability of selecting none of the correct six integers is ( 34 ( The same argument gives the answers in the other cases: ( 42 ( ( 50 ( 5.49 ( 58 ( Which is more likely: rolling a total of 8 when two dice are rolled or rolling a total of 8 when three dice are rolled? Solution. There are five ways to roll an 8 when two dice are rolled: (2,, (, 2, (3, 5, (5, 3, (4, 4; since there are 3 rolls possible, the probability of rolling an 8 is 5/ The ways to roll an 8 when three dice are rolled, before we consider reordering, are: (1, 1,, (1, 2, 5, (1, 3, 4, (2, 2, 4, (2, 3, 3 Two have three distinct numbers, and so can each happen in six ways. Three have two distinct numbers, and so can happen in three ways. This gives = 21 ways to roll an 8. Since there are 3 = 21 rolls possible, the probability of rolling an 8 is 21/ Thus it is more likely to roll a total of 8 when two dice are rolled than when three dice are rolled. 7
8 7.2.2 Find the probability of each outcome when a loaded die is rolled, if a 3 is twice as likely to appear as each of the other five numbers on one die. Solution. Let p be the probability of rolling a 1. The probability of 3 is 2p, and the probability of each other number is p. Since probabilities must add to 1, we have p + p + 2p + p + p + p = 1, so p = 1/7. Hence the probability of a 3 being rolled is 2/7, and the probability of any given other number being rolled is 1/ What is the probability of these events when we randomly select a permutation of {1, 2,..., n} where n 4? (a 1 precedes 2. Solution. The number of strings with 1 preceding 2 can be calculated ( as follows. Choose the two spots for 1 and 2; there are n 2 ways to do this. Then fill in the other other n 2 spaces with the remaining n 2 numbers; there are (n 2! ways to do this. This gives ( n 2 (n 2! ways to do this. Dividing by the n! permutations possible, this gives a probability of ( n 2 (n 2! n! = n(n 1/2 n(n 1 = 1/2. Alternative method: let A be the set of strings with 1 preceding 2, and B be the set of strings with 2 preceding 1. A and B are disjoint, and A B has all the strings. Moreover, A and B are in bijection: send a string to another string of A to a string of B by switching 1 and 2. Hence A and B are of the same size, so much each contain half of all strings. Thus the probability of choosing an element of A is 1/2. (b 2 precedes 1. Solution. A nigh-identical argument to part (a gives 1/2. (c 1 immediately precedes 2. 8
9 Solution. We may treat 1 and 2 as a single entity that moves as one, meaning we re permuting n 1 elements. There are (n 1! ways to do this, and so there are (n 1! permutations with 1 immediately preceding 2. Dividing by the n! permutations total gives a probability of 1/n that 1 immediately precedes 2. Alternative method: First we calculate the probability of 1 being in a position that has a number after it; all but the n th position do, so there s a probability of (n 1/n of this happening. Once we have this, we ask what the probability of 2 being in the correct spot is. Only one of the remaining n 1 spots is directly after 1, so there s a 1/(n 1 chance of this. Multiplying these gives us our probability of 1/n. (d n precedes 1 and n 1 precedes 2. Solution. Let s count up the number of strings satisfying this property. First we ll choose the four spots for 1, 2, n 1, and n. There are ( n 4 ways to do this. Then there are six orders we may place these four numbers into these four spots, giving us a factor of. Then we must fill in the remaining n 4 spots with the remaining n 4 numbers; there are (n 4! ways to do this. Multiplying together, there are ( n 4 (n 4! permutations with the desired property. Dividing by the n! total permutations gives a probability of ( n 4 (n 4! n(n 1(n 2(n 3/4! = = 1 n! n(n 1(n 2(n 3 4. Alternative method: the event n precedes 1 and n 1 precedes 2 are independent, and the probability of each is 1/2 (by part (a, so the probability of both is 1/2 1/2 = 1/4. (e n precedes 1 and n precedes 2. Solution. First we ll count up the number of strings where n precedes 1 and 1 precedes 2. First we ll choose the three spots for these numbers; there are ( n 3 ways to do this. Then we ll fill in the n 3 remaining spots; there are (n 3! ways to do this. This gives a total of ( n 3 (n 3! = n!/3! ways to do this. Now we ll count up the number of strings where n precedes 2 and 2 precedes 1. By symmetry, there are n!/3! strings like this. 9
10 Hence there are 2n!/3! = n!/3 strings with n preceding 1 and n preceding 2 (since either 1 precedes 2 or 2 precedes 1. This means the probability of a random permutation having n preceding 1 and n preceding 2 is n!/3 = 1 n! 3. Alternative method: there are six possible orderings for 1, 2, n. Let A i be the set of permutations containing 1, 2, n in the i th order, so that there are six sets, A 1, A 2,..., A. These sets are disjoint and A 1 A 2... A contains all the permutations. Moreover, A i is in bijection with A j for all i and j: send a string in A i to a string in A j with 1, 2, n switched to the appropriate ordering. Thus all the sets are the same size, and each must contain 1/ of all permutations. Since we re allowing two possible orderings, n 1 2 and n 2 1, the permutations we are interested in make up 1/ + 1/ = 1/3 of all permutations Show that if E and F are events, then p(e F p(e + p(f 1. Proof. Note that p(e F is at most 1, since it is a probability. Using the law of the excluded middle, this means that 1 p(e F = p(e + p(f p(e F. Adding p(e F to both sides gives as desired. p(e F p(e + p(f 1, ( Show that if E and F are independent events, then E and F are also independent events. Solution. We know that p(e F = p(ep(f, and we want to show that p ( E F = p ( E p ( F. 10
11 Using de Morgan s law, the rule of the excluded middle, and the independence of E and F, we have p ( E F =p ( E F as desired. =1 p (E F =1 p(e p(f + p(e F =1 p(e p(f + p(ep(f =(1 p(e(1 p(f =p ( E p ( F, What is the conditional probability that exactly four heads appear when a fair coin is flipped five times, given that the first flip came up tails? Solution. Let A be the event that exactly four heads appear, and let B be the event that the first flip comes up tails. We have p(a B = p(a B p(b = 1/25 1/2 = = Find each of the following probabilities when n independent Bernoulli trials are carried out with probability of success p. (a the probability of no successes. Solution. The probability of no successes is the probability of each outcome being a failure. Since each failure has probability (1 p, and the trials are independent, there is a probability of (1 p n of each outcome being a failure. (b the probability of at least one success. Solution. The complement of at least one success is no successes. The probabilities of these two outcomes must add to 1. We already calculated the probability of no successes as (1 p n, so the probability of at least one success is 1 (1 p n. (c the probability of at most one success. 11
12 Solution. The probability of exactly one success is np(1 p n 1 : there are n trials where the success could happen, and the probability of each such outcome is p(1 p n 1. We ve already calculated the probability of exactly zero successes as (1 p n. The probability of either zero or one is the probabilities added minus the probability of both happening; since both can t happen, we have a probability of np(1 p n 1 + (1 p n that there will be at most one success. (d the probability of at least two successes. Solution. This is the complement of at most one success. Hence its probability is 1 minus the answer from part (c, namely 1 np(1 p n 1 (1 p n. 12
Question: What is the probability that a five-card poker hand contains a flush, that is, five cards of the same suit?
ECS20 Discrete Mathematics Quarter: Spring 2007 Instructor: John Steinberger Assistant: Sophie Engle (prepared by Sophie Engle) Homework 8 Hints Due Wednesday June 6 th 2007 Section 6.1 #16 What is the
Discrete Math in Computer Science Homework 7 Solutions (Max Points: 80)
Discrete Math in Computer Science Homework 7 Solutions (Max Points: 80) CS 30, Winter 2016 by Prasad Jayanti 1. (10 points) Here is the famous Monty Hall Puzzle. Suppose you are on a game show, and you
Introductory Probability. MATH 107: Finite Mathematics University of Louisville. March 5, 2014
Introductory Probability MATH 07: Finite Mathematics University of Louisville March 5, 204 What is probability? Counting and probability 2 / 3 Probability in our daily lives We see chances, odds, and probabilities
Find the indicated probability. 1) If a single fair die is rolled, find the probability of a 4 given that the number rolled is odd.
Math 0 Practice Test 3 Fall 2009 Covers 7.5, 8.-8.3 MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question. Find the indicated probability. ) If a single
Probability. Sample space: all the possible outcomes of a probability experiment, i.e., the population of outcomes
Probability Basic Concepts: Probability experiment: process that leads to welldefined results, called outcomes Outcome: result of a single trial of a probability experiment (a datum) Sample space: all
Chapter 6. 1. What is the probability that a card chosen from an ordinary deck of 52 cards is an ace? Ans: 4/52.
Chapter 6 1. What is the probability that a card chosen from an ordinary deck of 52 cards is an ace? 4/52. 2. What is the probability that a randomly selected integer chosen from the first 100 positive
Lesson 1. Basics of Probability. Principles of Mathematics 12: Explained! www.math12.com 314
Lesson 1 Basics of Probability www.math12.com 314 Sample Spaces: Probability Lesson 1 Part I: Basic Elements of Probability Consider the following situation: A six sided die is rolled The sample space
Chapter 5 Section 2 day 1 2014f.notebook. November 17, 2014. Honors Statistics
Chapter 5 Section 2 day 1 2014f.notebook November 17, 2014 Honors Statistics Monday November 17, 2014 1 1. Welcome to class Daily Agenda 2. Please find folder and take your seat. 3. Review Homework C5#3
Discrete Mathematics and Probability Theory Fall 2009 Satish Rao, David Tse Note 10
CS 70 Discrete Mathematics and Probability Theory Fall 2009 Satish Rao, David Tse Note 10 Introduction to Discrete Probability Probability theory has its origins in gambling analyzing card games, dice,
Math 3C Homework 3 Solutions
Math 3C Homework 3 s Ilhwan Jo and Akemi Kashiwada [email protected], [email protected] Assignment: Section 2.3 Problems 2, 7, 8, 9,, 3, 5, 8, 2, 22, 29, 3, 32 2. You draw three cards from a standard
Lecture 1 Introduction Properties of Probability Methods of Enumeration Asrat Temesgen Stockholm University
Lecture 1 Introduction Properties of Probability Methods of Enumeration Asrat Temesgen Stockholm University 1 Chapter 1 Probability 1.1 Basic Concepts In the study of statistics, we consider experiments
Probability: The Study of Randomness Randomness and Probability Models. IPS Chapters 4 Sections 4.1 4.2
Probability: The Study of Randomness Randomness and Probability Models IPS Chapters 4 Sections 4.1 4.2 Chapter 4 Overview Key Concepts Random Experiment/Process Sample Space Events Probability Models Probability
36 Odds, Expected Value, and Conditional Probability
36 Odds, Expected Value, and Conditional Probability What s the difference between probabilities and odds? To answer this question, let s consider a game that involves rolling a die. If one gets the face
Definition and Calculus of Probability
In experiments with multivariate outcome variable, knowledge of the value of one variable may help predict another. For now, the word prediction will mean update the probabilities of events regarding the
STATISTICS 230 COURSE NOTES. Chris Springer, revised by Jerry Lawless and Don McLeish
STATISTICS 230 COURSE NOTES Chris Springer, revised by Jerry Lawless and Don McLeish JANUARY 2006 Contents 1. Introduction to Probability 1 2. Mathematical Probability Models 5 2.1 SampleSpacesandProbability...
Chapter 4 Lecture Notes
Chapter 4 Lecture Notes Random Variables October 27, 2015 1 Section 4.1 Random Variables A random variable is typically a real-valued function defined on the sample space of some experiment. For instance,
Probabilistic Strategies: Solutions
Probability Victor Xu Probabilistic Strategies: Solutions Western PA ARML Practice April 3, 2016 1 Problems 1. You roll two 6-sided dice. What s the probability of rolling at least one 6? There is a 1
Feb 7 Homework Solutions Math 151, Winter 2012. Chapter 4 Problems (pages 172-179)
Feb 7 Homework Solutions Math 151, Winter 2012 Chapter Problems (pages 172-179) Problem 3 Three dice are rolled. By assuming that each of the 6 3 216 possible outcomes is equally likely, find the probabilities
AP Stats - Probability Review
AP Stats - Probability Review Multiple Choice Identify the choice that best completes the statement or answers the question. 1. I toss a penny and observe whether it lands heads up or tails up. Suppose
V. RANDOM VARIABLES, PROBABILITY DISTRIBUTIONS, EXPECTED VALUE
V. RANDOM VARIABLES, PROBABILITY DISTRIBUTIONS, EXPETED VALUE A game of chance featured at an amusement park is played as follows: You pay $ to play. A penny and a nickel are flipped. You win $ if either
Contemporary Mathematics- MAT 130. Probability. a) What is the probability of obtaining a number less than 4?
Contemporary Mathematics- MAT 30 Solve the following problems:. A fair die is tossed. What is the probability of obtaining a number less than 4? What is the probability of obtaining a number less than
Discrete mathematics
Discrete mathematics Petr Kovář [email protected] VŠB Technical University of Ostrava DiM 470-2301/01, Winter term 2015/2016 About this file This file is meant to be a guideline for the lecturer. Many
Probability and Expected Value
Probability and Expected Value This handout provides an introduction to probability and expected value. Some of you may already be familiar with some of these topics. Probability and expected value are
Statistics 100A Homework 2 Solutions
Statistics Homework Solutions Ryan Rosario Chapter 9. retail establishment accepts either the merican Express or the VIS credit card. total of percent of its customers carry an merican Express card, 6
Lecture Note 1 Set and Probability Theory. MIT 14.30 Spring 2006 Herman Bennett
Lecture Note 1 Set and Probability Theory MIT 14.30 Spring 2006 Herman Bennett 1 Set Theory 1.1 Definitions and Theorems 1. Experiment: any action or process whose outcome is subject to uncertainty. 2.
Introduction to Discrete Probability. Terminology. Probability definition. 22c:19, section 6.x Hantao Zhang
Introduction to Discrete Probability 22c:19, section 6.x Hantao Zhang 1 Terminology Experiment A repeatable procedure that yields one of a given set of outcomes Rolling a die, for example Sample space
Lesson Plans for (9 th Grade Main Lesson) Possibility & Probability (including Permutations and Combinations)
Lesson Plans for (9 th Grade Main Lesson) Possibility & Probability (including Permutations and Combinations) Note: At my school, there is only room for one math main lesson block in ninth grade. Therefore,
ECE302 Spring 2006 HW1 Solutions January 16, 2006 1
ECE302 Spring 2006 HW1 Solutions January 16, 2006 1 Solutions to HW1 Note: These solutions were generated by R. D. Yates and D. J. Goodman, the authors of our textbook. I have added comments in italics
8.3 Probability Applications of Counting Principles
8. Probability Applications of Counting Principles In this section, we will see how we can apply the counting principles from the previous two sections in solving probability problems. Many of the probability
AP Statistics 7!3! 6!
Lesson 6-4 Introduction to Binomial Distributions Factorials 3!= Definition: n! = n( n 1)( n 2)...(3)(2)(1), n 0 Note: 0! = 1 (by definition) Ex. #1 Evaluate: a) 5! b) 3!(4!) c) 7!3! 6! d) 22! 21! 20!
Determine the empirical probability that a person selected at random from the 1000 surveyed uses Mastercard.
Math 120 Practice Exam II Name You must show work for credit. 1) A pair of fair dice is rolled 50 times and the sum of the dots on the faces is noted. Outcome 2 4 5 6 7 8 9 10 11 12 Frequency 6 8 8 1 5
MACM 101 Discrete Mathematics I
MACM 101 Discrete Mathematics I Exercises on Combinatorics, Probability, Languages and Integers. Due: Tuesday, November 2th (at the beginning of the class) Reminder: the work you submit must be your own.
Chapter 4 & 5 practice set. The actual exam is not multiple choice nor does it contain like questions.
Chapter 4 & 5 practice set. The actual exam is not multiple choice nor does it contain like questions. MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question.
MATHEMATICS 154, SPRING 2010 PROBABILITY THEORY Outline #3 (Combinatorics, bridge, poker)
Last modified: February, 00 References: MATHEMATICS 5, SPRING 00 PROBABILITY THEORY Outline # (Combinatorics, bridge, poker) PRP(Probability and Random Processes, by Grimmett and Stirzaker), Section.7.
Contemporary Mathematics Online Math 1030 Sample Exam I Chapters 12-14 No Time Limit No Scratch Paper Calculator Allowed: Scientific
Contemporary Mathematics Online Math 1030 Sample Exam I Chapters 12-14 No Time Limit No Scratch Paper Calculator Allowed: Scientific Name: The point value of each problem is in the left-hand margin. You
Discrete Mathematics and Probability Theory Fall 2009 Satish Rao, David Tse Note 13. Random Variables: Distribution and Expectation
CS 70 Discrete Mathematics and Probability Theory Fall 2009 Satish Rao, David Tse Note 3 Random Variables: Distribution and Expectation Random Variables Question: The homeworks of 20 students are collected
Random variables, probability distributions, binomial random variable
Week 4 lecture notes. WEEK 4 page 1 Random variables, probability distributions, binomial random variable Eample 1 : Consider the eperiment of flipping a fair coin three times. The number of tails that
Gaming the Law of Large Numbers
Gaming the Law of Large Numbers Thomas Hoffman and Bart Snapp July 3, 2012 Many of us view mathematics as a rich and wonderfully elaborate game. In turn, games can be used to illustrate mathematical ideas.
Responsible Gambling Education Unit: Mathematics A & B
The Queensland Responsible Gambling Strategy Responsible Gambling Education Unit: Mathematics A & B Outline of the Unit This document is a guide for teachers to the Responsible Gambling Education Unit:
Basic Probability. Probability: The part of Mathematics devoted to quantify uncertainty
AMS 5 PROBABILITY Basic Probability Probability: The part of Mathematics devoted to quantify uncertainty Frequency Theory Bayesian Theory Game: Playing Backgammon. The chance of getting (6,6) is 1/36.
Probability --QUESTIONS-- Principles of Math 12 - Probability Practice Exam 1 www.math12.com
Probability --QUESTIONS-- Principles of Math - Probability Practice Exam www.math.com Principles of Math : Probability Practice Exam Use this sheet to record your answers:... 4... 4... 4.. 6. 4.. 6. 7..
Statistics 100A Homework 8 Solutions
Part : Chapter 7 Statistics A Homework 8 Solutions Ryan Rosario. A player throws a fair die and simultaneously flips a fair coin. If the coin lands heads, then she wins twice, and if tails, the one-half
Elementary Statistics and Inference. Elementary Statistics and Inference. 16 The Law of Averages (cont.) 22S:025 or 7P:025.
Elementary Statistics and Inference 22S:025 or 7P:025 Lecture 20 1 Elementary Statistics and Inference 22S:025 or 7P:025 Chapter 16 (cont.) 2 D. Making a Box Model Key Questions regarding box What numbers
STAT 35A HW2 Solutions
STAT 35A HW2 Solutions http://www.stat.ucla.edu/~dinov/courses_students.dir/09/spring/stat35.dir 1. A computer consulting firm presently has bids out on three projects. Let A i = { awarded project i },
6.3 Conditional Probability and Independence
222 CHAPTER 6. PROBABILITY 6.3 Conditional Probability and Independence Conditional Probability Two cubical dice each have a triangle painted on one side, a circle painted on two sides and a square painted
MATH 140 Lab 4: Probability and the Standard Normal Distribution
MATH 140 Lab 4: Probability and the Standard Normal Distribution Problem 1. Flipping a Coin Problem In this problem, we want to simualte the process of flipping a fair coin 1000 times. Note that the outcomes
Combinatorial Proofs
Combinatorial Proofs Two Counting Principles Some proofs concerning finite sets involve counting the number of elements of the sets, so we will look at the basics of counting. Addition Principle: If A
Remarks on the Concept of Probability
5. Probability A. Introduction B. Basic Concepts C. Permutations and Combinations D. Poisson Distribution E. Multinomial Distribution F. Hypergeometric Distribution G. Base Rates H. Exercises Probability
Ch. 13.3: More about Probability
Ch. 13.3: More about Probability Complementary Probabilities Given any event, E, of some sample space, U, of a random experiment, we can always talk about the complement, E, of that event: this is the
Lecture 2 Binomial and Poisson Probability Distributions
Lecture 2 Binomial and Poisson Probability Distributions Binomial Probability Distribution l Consider a situation where there are only two possible outcomes (a Bernoulli trial) H Example: u flipping a
Unit 19: Probability Models
Unit 19: Probability Models Summary of Video Probability is the language of uncertainty. Using statistics, we can better predict the outcomes of random phenomena over the long term from the very complex,
Probabilities. Probability of a event. From Random Variables to Events. From Random Variables to Events. Probability Theory I
Victor Adamchi Danny Sleator Great Theoretical Ideas In Computer Science Probability Theory I CS 5-25 Spring 200 Lecture Feb. 6, 200 Carnegie Mellon University We will consider chance experiments with
If A is divided by B the result is 2/3. If B is divided by C the result is 4/7. What is the result if A is divided by C?
Problem 3 If A is divided by B the result is 2/3. If B is divided by C the result is 4/7. What is the result if A is divided by C? Suggested Questions to ask students about Problem 3 The key to this question
Sums of Independent Random Variables
Chapter 7 Sums of Independent Random Variables 7.1 Sums of Discrete Random Variables In this chapter we turn to the important question of determining the distribution of a sum of independent random variables
Math/Stats 342: Solutions to Homework
Math/Stats 342: Solutions to Homework Steven Miller ([email protected]) November 17, 2011 Abstract Below are solutions / sketches of solutions to the homework problems from Math/Stats 342: Probability
How To Solve The Social Studies Test
Math 00 Homework #0 Solutions. Section.: ab. For each map below, determine the number of southerly paths from point to point. Solution: We just have to use the same process as we did in building Pascal
Poker. 10,Jack,Queen,King,Ace. 10, Jack, Queen, King, Ace of the same suit Five consecutive ranks of the same suit that is not a 5,6,7,8,9
Poker Poker is an ideal setting to study probabilities. Computing the probabilities of different will require a variety of approaches. We will not concern ourselves with betting strategies, however. Our
Combinatorics. Chapter 1. 1.1 Factorials
Chapter 1 Combinatorics Copyright 2009 by David Morin, [email protected] (Version 4, August 30, 2009) This file contains the first three chapters (plus some appendices) of a potential book on Probability
Fundamentals of Probability
Fundamentals of Probability Introduction Probability is the likelihood that an event will occur under a set of given conditions. The probability of an event occurring has a value between 0 and 1. An impossible
Texas Hold em. From highest to lowest, the possible five card hands in poker are ranked as follows:
Texas Hold em Poker is one of the most popular card games, especially among betting games. While poker is played in a multitude of variations, Texas Hold em is the version played most often at casinos
Ch5: Discrete Probability Distributions Section 5-1: Probability Distribution
Recall: Ch5: Discrete Probability Distributions Section 5-1: Probability Distribution A variable is a characteristic or attribute that can assume different values. o Various letters of the alphabet (e.g.
Solutions: Problems for Chapter 3. Solutions: Problems for Chapter 3
Problem A: You are dealt five cards from a standard deck. Are you more likely to be dealt two pairs or three of a kind? experiment: choose 5 cards at random from a standard deck Ω = {5-combinations of
Section 7C: The Law of Large Numbers
Section 7C: The Law of Large Numbers Example. You flip a coin 00 times. Suppose the coin is fair. How many times would you expect to get heads? tails? One would expect a fair coin to come up heads half
Exam. Name. How many distinguishable permutations of letters are possible in the word? 1) CRITICS
Exam Name How many distinguishable permutations of letters are possible in the word? 1) CRITICS 2) GIGGLE An order of award presentations has been devised for seven people: Jeff, Karen, Lyle, Maria, Norm,
The New Mexico Lottery
The New Mexico Lottery 26 February 2014 Lotteries 26 February 2014 1/27 Today we will discuss the various New Mexico Lottery games and look at odds of winning and the expected value of playing the various
Hoover High School Math League. Counting and Probability
Hoover High School Math League Counting and Probability Problems. At a sandwich shop there are 2 kinds of bread, 5 kinds of cold cuts, 3 kinds of cheese, and 2 kinds of dressing. How many different sandwiches
Solution. Solution. (a) Sum of probabilities = 1 (Verify) (b) (see graph) Chapter 4 (Sections 4.3-4.4) Homework Solutions. Section 4.
Math 115 N. Psomas Chapter 4 (Sections 4.3-4.4) Homework s Section 4.3 4.53 Discrete or continuous. In each of the following situations decide if the random variable is discrete or continuous and give
The Normal Approximation to Probability Histograms. Dice: Throw a single die twice. The Probability Histogram: Area = Probability. Where are we going?
The Normal Approximation to Probability Histograms Where are we going? Probability histograms The normal approximation to binomial histograms The normal approximation to probability histograms of sums
1 Combinations, Permutations, and Elementary Probability
1 Combinations, Permutations, and Elementary Probability Roughly speaking, Permutations are ways of grouping things where the order is important. Combinations are ways of grouping things where the order
Name: Date: Use the following to answer questions 2-4:
Name: Date: 1. A phenomenon is observed many, many times under identical conditions. The proportion of times a particular event A occurs is recorded. What does this proportion represent? A) The probability
Session 8 Probability
Key Terms for This Session Session 8 Probability Previously Introduced frequency New in This Session binomial experiment binomial probability model experimental probability mathematical probability outcome
Exam 3 Review/WIR 9 These problems will be started in class on April 7 and continued on April 8 at the WIR.
Exam 3 Review/WIR 9 These problems will be started in class on April 7 and continued on April 8 at the WIR. 1. Urn A contains 6 white marbles and 4 red marbles. Urn B contains 3 red marbles and two white
Section 6.2 Definition of Probability
Section 6.2 Definition of Probability Probability is a measure of the likelihood that an event occurs. For example, if there is a 20% chance of rain tomorrow, that means that the probability that it will
Binomial random variables (Review)
Poisson / Empirical Rule Approximations / Hypergeometric Solutions STAT-UB.3 Statistics for Business Control and Regression Models Binomial random variables (Review. Suppose that you are rolling a die
Practical Probability:
Practical Probability: Casino Odds and Sucker Bets Tom Davis [email protected] April 2, 2011 Abstract Gambling casinos are there to make money, so in almost every instance, the games you can bet
Introduction to Probability
Massachusetts Institute of Technology Course Notes 0 6.04J/8.06J, Fall 0: Mathematics for Computer Science November 4 Professor Albert Meyer and Dr. Radhika Nagpal revised November 6, 00, 57 minutes Introduction
MA 1125 Lecture 14 - Expected Values. Friday, February 28, 2014. Objectives: Introduce expected values.
MA 5 Lecture 4 - Expected Values Friday, February 2, 24. Objectives: Introduce expected values.. Means, Variances, and Standard Deviations of Probability Distributions Two classes ago, we computed the
Rules of core casino games in Great Britain
Rules of core casino games in Great Britain June 2011 Contents 1 Introduction 3 2 American Roulette 4 3 Blackjack 5 4 Punto Banco 7 5 Three Card Poker 9 6 Dice/Craps 11 2 1 Introduction 1.1 This document
6th Grade Lesson Plan: Probably Probability
6th Grade Lesson Plan: Probably Probability Overview This series of lessons was designed to meet the needs of gifted children for extension beyond the standard curriculum with the greatest ease of use
In the situations that we will encounter, we may generally calculate the probability of an event
What does it mean for something to be random? An event is called random if the process which produces the outcome is sufficiently complicated that we are unable to predict the precise result and are instead
Math 55: Discrete Mathematics
Math 55: Discrete Mathematics UC Berkeley, Fall 2011 Homework # 5, due Wednesday, February 22 5.1.4 Let P (n) be the statement that 1 3 + 2 3 + + n 3 = (n(n + 1)/2) 2 for the positive integer n. a) What
Coin Flip Questions. Suppose you flip a coin five times and write down the sequence of results, like HHHHH or HTTHT.
Coin Flip Questions Suppose you flip a coin five times and write down the sequence of results, like HHHHH or HTTHT. 1 How many ways can you get exactly 1 head? 2 How many ways can you get exactly 2 heads?
5. Probability Calculus
5. Probability Calculus So far we have concentrated on descriptive statistics (deskriptiivinen eli kuvaileva tilastotiede), that is methods for organizing and summarizing data. As was already indicated
(b) You draw two balls from an urn and track the colors. When you start, it contains three blue balls and one red ball.
Examples for Chapter 3 Probability Math 1040-1 Section 3.1 1. Draw a tree diagram for each of the following situations. State the size of the sample space. (a) You flip a coin three times. (b) You draw
Probability definitions
Probability definitions 1. Probability of an event = chance that the event will occur. 2. Experiment = any action or process that generates observations. In some contexts, we speak of a data-generating
Random Fibonacci-type Sequences in Online Gambling
Random Fibonacci-type Sequences in Online Gambling Adam Biello, CJ Cacciatore, Logan Thomas Department of Mathematics CSUMS Advisor: Alfa Heryudono Department of Mathematics University of Massachusetts
Chapter 5: Probability
Chapter 5: Probability 5.1 What is probability anyway? Probability is a branch of mathematics which intrudes on everyday conversation perhaps more than any other (except for just plain arithmetic and counting).
Mathematical Expectation
Mathematical Expectation Properties of Mathematical Expectation I The concept of mathematical expectation arose in connection with games of chance. In its simplest form, mathematical expectation is the
IAM 530 ELEMENTS OF PROBABILITY AND STATISTICS INTRODUCTION
IAM 530 ELEMENTS OF PROBABILITY AND STATISTICS INTRODUCTION 1 WHAT IS STATISTICS? Statistics is a science of collecting data, organizing and describing it and drawing conclusions from it. That is, statistics
That s Not Fair! ASSESSMENT #HSMA20. Benchmark Grades: 9-12
That s Not Fair! ASSESSMENT # Benchmark Grades: 9-12 Summary: Students consider the difference between fair and unfair games, using probability to analyze games. The probability will be used to find ways
Question 1 Formatted: Formatted: Formatted: Formatted:
In many situations in life, we are presented with opportunities to evaluate probabilities of events occurring and make judgments and decisions from this information. In this paper, we will explore four
Homework 8 Solutions
CSE 21 - Winter 2014 Homework Homework 8 Solutions 1 Of 330 male and 270 female employees at the Flagstaff Mall, 210 of the men and 180 of the women are on flex-time (flexible working hours). Given that
STAT 319 Probability and Statistics For Engineers PROBABILITY. Engineering College, Hail University, Saudi Arabia
STAT 319 robability and Statistics For Engineers LECTURE 03 ROAILITY Engineering College, Hail University, Saudi Arabia Overview robability is the study of random events. The probability, or chance, that
Lecture 3: One-Way Encryption, RSA Example
ICS 180: Introduction to Cryptography April 13, 2004 Lecturer: Stanislaw Jarecki Lecture 3: One-Way Encryption, RSA Example 1 LECTURE SUMMARY We look at a different security property one might require
Math 141. Lecture 2: More Probability! Albyn Jones 1. [email protected] www.people.reed.edu/ jones/courses/141. 1 Library 304. Albyn Jones Math 141
Math 141 Lecture 2: More Probability! Albyn Jones 1 1 Library 304 [email protected] www.people.reed.edu/ jones/courses/141 Outline Law of total probability Bayes Theorem the Multiplication Rule, again Recall
Discrete Structures for Computer Science
Discrete Structures for Computer Science Adam J. Lee [email protected] 6111 Sennott Square Lecture #20: Bayes Theorem November 5, 2013 How can we incorporate prior knowledge? Sometimes we want to know
Probabilities of Poker Hands with Variations
Probabilities of Poker Hands with Variations Jeff Duda Acknowledgements: Brian Alspach and Yiu Poon for providing a means to check my numbers Poker is one of the many games involving the use of a 52-card
Bayesian Tutorial (Sheet Updated 20 March)
Bayesian Tutorial (Sheet Updated 20 March) Practice Questions (for discussing in Class) Week starting 21 March 2016 1. What is the probability that the total of two dice will be greater than 8, given that
Probability Using Dice
Using Dice One Page Overview By Robert B. Brown, The Ohio State University Topics: Levels:, Statistics Grades 5 8 Problem: What are the probabilities of rolling various sums with two dice? How can you
COMMON CORE STATE STANDARDS FOR
COMMON CORE STATE STANDARDS FOR Mathematics (CCSSM) High School Statistics and Probability Mathematics High School Statistics and Probability Decisions or predictions are often based on data numbers in
