Homework 10 Solution Section 4.2, 4.3.

Size: px
Start display at page:

Download "Homework 10 Solution Section 4.2, 4.3."

Transcription

1 MATH 00 Homewor Homewor 0 Solution Section.,.3. Please read your writing again before moving to the next roblem. Do not abbreviate your answer. Write everything in full sentences. Write your answer neatly. If I couldn t understand it, you ll get 0 oint. You may discuss with your classmates. But do not coy directly.. There is a boo club consisting of 6 male students and female students. The members want to select a committee consisting of four students. a Find the number of ways to mae the committee b How many ways to mae a four-erson committee consisting of two male students and two female students are ossible? c How many ways to mae a four-erson committee with at least two female students are ossible? d How many ways to mae a four-erson committee consisting of a resident, a vice-resident, a secretary, and a treasurer? In this roblem, the order of selection matters. 8P 8!! 900. In an ad for Pizza Hut, Jessica Simson exlains to the Muets that there are more than 6 million ossibilities for their forall Pizza. Unfortunately, I was unabled to find the video cli of this commercial, but here is another version in 00: clic here to watch

2 MATH 00 Homewor a Each izza can have u to 3 toings, out of 7 ossible choices, or can be one of four secialty izzas. Calculate the number of different izzas ossible. 7 The number of izzas with toings is. Because there are seciality izzas, the total number is b Out of the total ossible izza calculated in the first art of this exercise, a forall Pizza consists of four izzas in a box you may order some same ind izzas. Calculate the total number of forall Pizzas ossible. Comare with her comutation. To mae a box, we have to choose four izzas. The order of selection is not imortant, and reetition is allowed. Therefore the number of selection is , 695, 8, 670, which is way larger than her comutation. 3. a Prove the following equality by using algebra. n n n. n n!!n! n!!n! n!!n! nn!!n! n n!!n! n b Prove the same equality by using combinatorial idea. n Consider the situation counting the number of ways to select a -erson committee, and a chair in the selected committee from a grou of n eole. We will count the number of ways in two different ways. n First of all, the number of ways to select such a committee is. The number of ways to select a chair is. Thus the total number of ways n is. On the other hand, we may select a chair first, and then select the remaining committee members. Then the number of ways to choose a chair is

3 MATH 00 Homewor n n, and the number of ways to select remaining members is. n Therefore the total number is n. These two numbers must be same because they are counting the same number of ways. Therefore n. n n. Prove the following equality by using combinatorial idea. r 0 r s n r s Suose that there are r men and s women. We will comute the number of ways r s to select n eole, without regarding the order. This number is. n On the other hand, in this selected grou, the number of men can be any integer from 0 to r. In the case that the number of men is, there must be n r s women, so the number of ways to choose a grou is. By adding all n of the numbers for 0,,, r, we can obtain the total number of selections. Therefore, r r s r s. n n 0 5. Let be a rime number. a Show that is a multile of for 0 < <. Note that!!!. On the right hand side, on the numerator, is a divisor. If 0,, then every factor on the denominator is an integer less than. Because is a rime number, none of the factors of denominator divides. Therefore it is a multile of. b By using induction on n, rove that n n. Hint: For the inductive ste with induction hyothesis, use binomial theorem on. Then aly a. Let n. Then n n 0. Because 0, this case is true. Suose that n case is true. Then. By binomial theorem, 3 i0 n i i

4 MATH 00 Homewor 0. By a, s on the right hand side are all multiles of. By induction i hyothesis, is also a multile of. Therefore it is a multile of. 6. Let n N. Prove that the number of artitions of n equals the number of artitions of n with recisely n arts. I recommend to list all relevant artitions for n 3,, 5, 6 and try to mae exlicit bijections. Let P n be the set of artitions of n, and let P n,n be the set of artitions of n with n arts. Define a function f : P n,n P n as the following. For a, a,, a n P n,n, consider a new sequence b, b,, b which is obtained from a, a,, a n by discarding all 0 s. Define fa, a,, a n b, b,, b. We claim that f is a bijective function. The simlest way to chec it is constructing its inverse function. Let g : P n P n,n be a function defined by gb, b,, b b, b,, b,,,, the result is a sequence of length n. It is straightforward to chec that g is the inverse of f. Since f is bijective, P n P n,n. 7. There are n eole resent in a room. Prove that among them there are two eole who have the same number of acquaintances in the room. Here is a urely grah theoretic interretation of the same roblem. Let G be a simle grah with n vertices. Prove that there are two vertices with the same degree. Let X be the set of n eole in the room and let Y {0,,,, n }. Define a function f : X Y as fx the number of acquaintances. Suose first, that there is no erson with no acquaintance. Then we may use Y {,,, n } as the codomain instead of Y. Then X n and Y n, so X > Y. By igeonhole rincile, f is not an injective function. So there are a, b X so that fa fb. This means there are two eole with the same number of acquaintances. Now suose that there is a erson x with no acquaintance. If there is a erson y with n acquaintances, then x and y must now each other. It contradicts to the fact that x has no acquaintance. Therefore there is no erson with n acquaintances. So we may relace the codomain Y by Y {0,,,, n }.

5 MATH 00 Homewor Then again, X > Y. So by the same argument, we can conclude that there are two eole with the same number of acquaintances. 8. Show that among 3 eole, there are two born in the same month. Let X be the set of those 3 eole and let Y be the set of months. Let f : X Y be a function that fx the month that x was born. Then X 3 and Y. By igeonhole rincile, there are a, b X such that fa fb. So there are two eole who were born in the same month. Below is a set of exercise roblems for Chater, including the last section.. They are not homewor. This list may be udated. 9. By using combinatorial idea, show that n r r for any three natural numbers r n. n n r 0. Recall that from the binomial theorem. x n n r0 n x r r a By using algebra and calculus, show that n n r n n. r r0 Hint: Tae the derivative of. b By using combinatorial idea, rove the same equality.. Let a, b be two corime natural numbers. Show that the decimal reresentation of a/b has at most eriod b.. A target has the form of an equilateral triangle with side. Prove that if it is hit 5 times, then there will be two holes with distance. 3. Suose that there are distinct two-digit natural numbers n, n,, n. Show that there are two numbers whose difference is of the form aa.. Let a, a,, a n be n integers. Prove that there always exists a subset of these numbers with sum divisible by n. 5

6 MATH 00 Homewor 5. A controversy arose in 99 over the Teen Tal Barbie doll, each of which was rogrammed with four sayings randomly iced from a set of 70 sayings. The controversy ways over the saying, Math class is tough, which some felt gave a negative message toward girls doing well in math. In an interview with Science, a soeswoman for Mattel, the maers of Barbie, said that There s a less than % chance you re going to get a doll that says math class is tough. Is this figure correct? If not, give the correct figure. 6. During the 009 season, the Washington Nationals baseball team won 59 games and lost 03 games. Season ticet holder Stehen Kruin reorted in an interview that he watched the team lose all 9 games that he attended that season. The interviewer seculated that this must be a record for bad luc. a Based on the full 009 season record, calculate the robability that a erson would attend 9 Washington Nationals games and the Nationals would lose all 9 games. b However, Mr. Kruin only attended home games. The Nationals has 33 wins and 8 losses at home in 009. Calculate the robability that a erson would attend 9 Washington Nationals home games and the Nationals would lose all 9 games. 7. Suose that 3 edges of K n are chosen at random. Find the robability that these edges form a triangle. 8. Suose that 3 eole are in a classroom. a Find the robability that their birthdays are all different. b Find the robability that there are two eole with the same birthday. 6

and their probabilities p

and their probabilities p AP Statistics Ch. 6 Notes Random Variables A variable is any characteristic of an individual (remember that individuals are the objects described by a data set and may be eole, animals, or things). Variables

More information

Objectives. 5.2, 8.1 Inference for a single proportion. Categorical data from a simple random sample. Binomial distribution

Objectives. 5.2, 8.1 Inference for a single proportion. Categorical data from a simple random sample. Binomial distribution Objectives 5.2, 8.1 Inference for a single roortion Categorical data from a simle random samle Binomial distribution Samling distribution of the samle roortion Significance test for a single roortion Large-samle

More information

Lecture 2. Main Topics: (Part II) Chapter 2 (2-7), Chapter 3. Bayes Theorem: Let A, B be two events, then. The probabilities P ( B), probability of B.

Lecture 2. Main Topics: (Part II) Chapter 2 (2-7), Chapter 3. Bayes Theorem: Let A, B be two events, then. The probabilities P ( B), probability of B. STT315, Section 701, Summer 006 Lecture (Part II) Main Toics: Chater (-7), Chater 3. Bayes Theorem: Let A, B be two events, then B A) = A B) B) A B) B) + A B) B) The robabilities P ( B), B) are called

More information

Policyholder Outcome Death Disability Neither Payout, x 10,000 5, ,000

Policyholder Outcome Death Disability Neither Payout, x 10,000 5, ,000 Two tyes of Random Variables: ) Discrete random variable has a finite number of distinct outcomes Examle: Number of books this term. ) Continuous random variable can take on any numerical value within

More information

Asian Economic and Financial Review A MODEL FOR ESTIMATING THE DISTRIBUTION OF FUTURE POPULATION. Ben David Nissim.

Asian Economic and Financial Review A MODEL FOR ESTIMATING THE DISTRIBUTION OF FUTURE POPULATION. Ben David Nissim. Asian Economic and Financial Review journal homeage: htt://www.aessweb.com/journals/5 A MODEL FOR ESTIMATING THE DISTRIBUTION OF FUTURE POPULATION Ben David Nissim Deartment of Economics and Management,

More information

Objectives. 3.3 Toward statistical inference

Objectives. 3.3 Toward statistical inference Objectives 3.3 Toward statistical inference Poulation versus samle (CIS, Chater 6) Toward statistical inference Samling variability Further reading: htt://onlinestatbook.com/2/estimation/characteristics.html

More information

INDEX NUMBERS. Introduction

INDEX NUMBERS. Introduction INDEX NUMBERS Introduction Index numbers are the indicators which reflect changes over a secified eriod of time in rices of different commodities industrial roduction (iii) sales (iv) imorts and exorts

More information

MAC Learning Objectives. Learning Objectives (Cont.)

MAC Learning Objectives. Learning Objectives (Cont.) MAC 1140 Module 12 Introduction to Sequences, Counting, The Binomial Theorem, and Mathematical Induction Learning Objectives Upon completing this module, you should be able to 1. represent sequences. 2.

More information

Ordering a deck of cards... Lecture 3: Binomial Distribution. Example. Permutations & Combinations

Ordering a deck of cards... Lecture 3: Binomial Distribution. Example. Permutations & Combinations Ordering a dec of cards... Lecture 3: Binomial Distribution Sta 111 Colin Rundel May 16, 2014 If you have ever shuffled a dec of cards you have done something no one else has ever done before or will ever

More information

The Binomial Theorem and Consequences

The Binomial Theorem and Consequences The Binomial Theorem and Consequences Juris Steprāns York University November 17, 2011 Fermat s Theorem Pierre de Fermat claimed the following theorem in 1640, but the first published proof (by Leonhard

More information

Supplemental Material: Buyer-Optimal Learning and Monopoly Pricing

Supplemental Material: Buyer-Optimal Learning and Monopoly Pricing Sulemental Material: Buyer-Otimal Learning and Monooly Pricing Anne-Katrin Roesler and Balázs Szentes February 3, 207 The goal of this note is to characterize buyer-otimal outcomes with minimal learning

More information

6.1 Binomial Theorem

6.1 Binomial Theorem Unit 6 Probability AFM Valentine 6.1 Binomial Theorem Objective: I will be able to read and evaluate binomial coefficients. I will be able to expand binomials using binomial theorem. Vocabulary Binomial

More information

Lecture 2. Multinomial coefficients and more counting problems

Lecture 2. Multinomial coefficients and more counting problems 18.440: Lecture 2 Multinomial coefficients and more counting problems Scott Sheffield MIT 1 Outline Multinomial coefficients Integer partitions More problems 2 Outline Multinomial coefficients Integer

More information

Math 160 Professor Busken Chapter 5 Worksheets

Math 160 Professor Busken Chapter 5 Worksheets Math 160 Professor Busken Chapter 5 Worksheets Name: 1. Find the expected value. Suppose you play a Pick 4 Lotto where you pay 50 to select a sequence of four digits, such as 2118. If you select the same

More information

As last year drew to a close, the December tax overhaul got a lot of

As last year drew to a close, the December tax overhaul got a lot of How the New Tax Law Affects Your Estate Plan An udate to Estate Planning Smarts, 4th Edition By Deborah L. Jacobs As last year drew to a close, the December tax overhaul got a lot of attention. The first

More information

NMAI059 Probability and Statistics Exercise assignments and supplementary examples October 21, 2017

NMAI059 Probability and Statistics Exercise assignments and supplementary examples October 21, 2017 NMAI059 Probability and Statistics Exercise assignments and supplementary examples October 21, 2017 How to use this guide. This guide is a gradually produced text that will contain key exercises to practise

More information

2/20/2013. of Manchester. The University COMP Building a yes / no classifier

2/20/2013. of Manchester. The University COMP Building a yes / no classifier COMP4 Lecture 6 Building a yes / no classifier Buildinga feature-basedclassifier Whatis a classifier? What is an information feature? Building a classifier from one feature Probability densities and the

More information

Games with more than 1 round

Games with more than 1 round Games with more than round Reeated risoner s dilemma Suose this game is to be layed 0 times. What should you do? Player High Price Low Price Player High Price 00, 00-0, 00 Low Price 00, -0 0,0 What if

More information

CONSUMER CREDIT SCHEME OF PRIVATE COMMERCIAL BANKS: CONSUMERS PREFERENCE AND FEEDBACK

CONSUMER CREDIT SCHEME OF PRIVATE COMMERCIAL BANKS: CONSUMERS PREFERENCE AND FEEDBACK htt://www.researchersworld.com/ijms/ CONSUMER CREDIT SCHEME OF PRIVATE COMMERCIAL BANKS: CONSUMERS PREFERENCE AND FEEDBACK Rania Kabir, Lecturer, Primeasia University, Bangladesh. Ummul Wara Adrita, Lecturer,

More information

Chapter 1: Stochastic Processes

Chapter 1: Stochastic Processes Chater 1: Stochastic Processes 4 What are Stochastic Processes, and how do they fit in? STATS 210 Foundations of Statistics and Probability Tools for understanding randomness (random variables, distributions)

More information

Ex 1) Suppose a license plate can have any three letters followed by any four digits.

Ex 1) Suppose a license plate can have any three letters followed by any four digits. AFM Notes, Unit 1 Probability Name 1-1 FPC and Permutations Date Period ------------------------------------------------------------------------------------------------------- The Fundamental Principle

More information

3 Ways to Write Ratios

3 Ways to Write Ratios RATIO & PROPORTION Sec 1. Defining Ratio & Proportion A RATIO is a comparison between two quantities. We use ratios everyday; one Pepsi costs 50 cents describes a ratio. On a map, the legend might tell

More information

3 Ways to Write Ratios

3 Ways to Write Ratios RATIO & PROPORTION Sec 1. Defining Ratio & Proportion A RATIO is a comparison between two quantities. We use ratios every day; one Pepsi costs 50 cents describes a ratio. On a map, the legend might tell

More information

Exercises for Chapter (5)

Exercises for Chapter (5) Exercises for Chapter (5) MULTILE CHOICE. Choose the one alternative that best completes the statement or answers the question. 1) 500 families were interviewed and the number of children per family was

More information

C (1,1) (1,2) (2,1) (2,2)

C (1,1) (1,2) (2,1) (2,2) TWO COIN MORRA This game is layed by two layers, R and C. Each layer hides either one or two silver dollars in his/her hand. Simultaneously, each layer guesses how many coins the other layer is holding.

More information

Chapter 7 Probability

Chapter 7 Probability Chapter 7 Probability Copyright 2004 Brooks/Cole, a division of Thomson Learning, Inc. 7.1 Random Circumstances Random circumstance is one in which the outcome is unpredictable. Case Study 1.1 Alicia Has

More information

Permutations, Combinations And Binomial Theorem Exam Questions

Permutations, Combinations And Binomial Theorem Exam Questions Permutations, Combinations And Binomial Theorem Exam Questions Name: ANSWERS Multiple Choice 1. Find the total possible arrangements for 7 adults and 3 children seated in a row if the 3 children must

More information

Chapter 15 - The Binomial Formula PART

Chapter 15 - The Binomial Formula PART Chapter 15 - The Binomial Formula PART IV : PROBABILITY Dr. Joseph Brennan Math 148, BU Dr. Joseph Brennan (Math 148, BU) Chapter 15 - The Binomial Formula 1 / 19 Pascal s Triangle In this chapter we explore

More information

Mean, Variance, and Expectation. Mean

Mean, Variance, and Expectation. Mean 3 Mean, Variance, and Expectation The mean, variance, and standard deviation for a probability distribution are computed differently from the mean, variance, and standard deviation for samples. This section

More information

A relation on 132-avoiding permutation patterns

A relation on 132-avoiding permutation patterns Discrete Mathematics and Theoretical Computer Science DMTCS vol. VOL, 205, 285 302 A relation on 32-avoiding permutation patterns Natalie Aisbett School of Mathematics and Statistics, University of Sydney,

More information

: now we have a family of utility functions for wealth increments z indexed by initial wealth w.

: now we have a family of utility functions for wealth increments z indexed by initial wealth w. Lotteries with Money Payoffs, continued Fix u, let w denote wealth, and set u ( z) u( z w) : now we have a family of utility functions for wealth increments z indexed by initial wealth w. (a) Recall from

More information

What do you think "Binomial" involves?

What do you think Binomial involves? Learning Goals: * Define a binomial experiment (Bernoulli Trials). * Applying the binomial formula to solve problems. * Determine the expected value of a Binomial Distribution What do you think "Binomial"

More information

Midterm Exam III Review

Midterm Exam III Review Midterm Exam III Review Dr. Joseph Brennan Math 148, BU Dr. Joseph Brennan (Math 148, BU) Midterm Exam III Review 1 / 25 Permutations and Combinations ORDER In order to count the number of possible ways

More information

On the smallest abundant number not divisible by the first k primes

On the smallest abundant number not divisible by the first k primes On the smallest abundant number not divisible by the first k rimes Douglas E. Iannucci Abstract We say a ositive integer n is abundant if σ(n) > 2n, where σ(n) denotes the sum of the ositive divisors of

More information

EconS Intermediate Microeconomics without Calculus Set 2 Homework Solutions

EconS Intermediate Microeconomics without Calculus Set 2 Homework Solutions Econ - Intermediate Microeconomics without Calculus et Homework olutions Assignment &. Consider the market for football tickets. It faces the following suly and demand functions = + = 8 + Y + B where is

More information

The Binomial Theorem 5.4

The Binomial Theorem 5.4 54 The Binomial Theorem Recall that a binomial is a polynomial with just two terms, so it has the form a + b Expanding (a + b) n becomes very laborious as n increases This section introduces a method for

More information

Non-Inferiority Tests for the Ratio of Two Correlated Proportions

Non-Inferiority Tests for the Ratio of Two Correlated Proportions Chater 161 Non-Inferiority Tests for the Ratio of Two Correlated Proortions Introduction This module comutes ower and samle size for non-inferiority tests of the ratio in which two dichotomous resonses

More information

Algebra homework 8 Homomorphisms, isomorphisms

Algebra homework 8 Homomorphisms, isomorphisms MATH-UA.343.005 T.A. Louis Guigo Algebra homework 8 Homomorphisms, isomorphisms For every n 1 we denote by S n the n-th symmetric group. Exercise 1. Consider the following permutations: ( ) ( 1 2 3 4 5

More information

(Practice Version) Midterm Exam 1

(Practice Version) Midterm Exam 1 EECS 126 Probability and Random Processes University of California, Berkeley: Fall 2014 Kannan Ramchandran September 19, 2014 (Practice Version) Midterm Exam 1 Last name First name SID Rules. DO NOT open

More information

Interest Math A. Miller December 16, The Formulas

Interest Math A. Miller December 16, The Formulas Interest Math A. Miller December 16, 2008 1 The Formulas Arnold W. Miller The Mathematics of Interest Rates There are only two formulas needed to calculate everything in this subject. One is the geometric

More information

Quantitative Aggregate Effects of Asymmetric Information

Quantitative Aggregate Effects of Asymmetric Information Quantitative Aggregate Effects of Asymmetric Information Pablo Kurlat February 2012 In this note I roose a calibration of the model in Kurlat (forthcoming) to try to assess the otential magnitude of the

More information

Multinomial Coefficient : A Generalization of the Binomial Coefficient

Multinomial Coefficient : A Generalization of the Binomial Coefficient Multinomial Coefficient : A Generalization of the Binomial Coefficient Example: A team plays 16 games in a season. At the end of the season, the team has 8 wins, 3 ties and 5 losses. How many different

More information

MATH1215: Mathematical Thinking Sec. 08 Spring Worksheet 9: Solution. x P(x)

MATH1215: Mathematical Thinking Sec. 08 Spring Worksheet 9: Solution. x P(x) N. Name: MATH: Mathematical Thinking Sec. 08 Spring 0 Worksheet 9: Solution Problem Compute the expected value of this probability distribution: x 3 8 0 3 P(x) 0. 0.0 0.3 0. Clearly, a value is missing

More information

LECTURE NOTES ON MICROECONOMICS

LECTURE NOTES ON MICROECONOMICS LECTURE NOTES ON MCROECONOMCS ANALYZNG MARKETS WTH BASC CALCULUS William M. Boal Part : Consumers and demand Chater 5: Demand Section 5.: ndividual demand functions Determinants of choice. As noted in

More information

Brownian Motion, the Gaussian Lévy Process

Brownian Motion, the Gaussian Lévy Process Brownian Motion, the Gaussian Lévy Process Deconstructing Brownian Motion: My construction of Brownian motion is based on an idea of Lévy s; and in order to exlain Lévy s idea, I will begin with the following

More information

MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question.

MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question. First Name: Last Name: SID: Class Time: M Tu W Th math10 - HW3 MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question. 1) Continuous random variables are

More information

Dr. Maddah ENMG 625 Financial Eng g II 10/16/06. Chapter 11 Models of Asset Dynamics (1)

Dr. Maddah ENMG 625 Financial Eng g II 10/16/06. Chapter 11 Models of Asset Dynamics (1) Dr Maddah ENMG 65 Financial Eng g II 0/6/06 Chater Models of Asset Dynamics () Overview Stock rice evolution over time is commonly modeled with one of two rocesses: The binomial lattice and geometric Brownian

More information

Chapter Chapter 6. Modeling Random Events: The Normal and Binomial Models

Chapter Chapter 6. Modeling Random Events: The Normal and Binomial Models Chapter 6 107 Chapter 6 Modeling Random Events: The Normal and Binomial Models Chapter 6 108 Chapter 6 109 Table Number: Group Name: Group Members: Discrete Probability Distribution: Ichiro s Hit Parade

More information

The Real Numbers. Here we show one way to explicitly construct the real numbers R. First we need a definition.

The Real Numbers. Here we show one way to explicitly construct the real numbers R. First we need a definition. The Real Numbers Here we show one way to explicitly construct the real numbers R. First we need a definition. Definitions/Notation: A sequence of rational numbers is a funtion f : N Q. Rather than write

More information

CS522 - Exotic and Path-Dependent Options

CS522 - Exotic and Path-Dependent Options CS522 - Exotic and Path-Deendent Otions Tibor Jánosi May 5, 2005 0. Other Otion Tyes We have studied extensively Euroean and American uts and calls. The class of otions is much larger, however. A digital

More information

Example 1: Identify the following random variables as discrete or continuous: a) Weight of a package. b) Number of students in a first-grade classroom

Example 1: Identify the following random variables as discrete or continuous: a) Weight of a package. b) Number of students in a first-grade classroom Section 5-1 Probability Distributions I. Random Variables A variable x is a if the value that it assumes, corresponding to the of an experiment, is a or event. A random variable is if it potentially can

More information

Individual Comparative Advantage and Human Capital Investment under Uncertainty

Individual Comparative Advantage and Human Capital Investment under Uncertainty Individual Comarative Advantage and Human Caital Investment under Uncertainty Toshihiro Ichida Waseda University July 3, 0 Abstract Secialization and the division of labor are the sources of high roductivity

More information

Application of Monte-Carlo Tree Search to Traveling-Salesman Problem

Application of Monte-Carlo Tree Search to Traveling-Salesman Problem R4-14 SASIMI 2016 Proceedings Alication of Monte-Carlo Tree Search to Traveling-Salesman Problem Masato Shimomura Yasuhiro Takashima Faculty of Environmental Engineering University of Kitakyushu Kitakyushu,

More information

Unit 9 Day 4. Agenda Questions from Counting (last class)? Recall Combinations and Factorial Notation!! 2. Simplify: Recall (a + b) n

Unit 9 Day 4. Agenda Questions from Counting (last class)? Recall Combinations and Factorial Notation!! 2. Simplify: Recall (a + b) n Unit 9 Day 4 Agenda Questions from Counting (last class)? Recall Combinations and Factorial Notation 1. Simplify:!! 2. Simplify: 2 Recall (a + b) n Sec 12.6 un9act4: Binomial Experiment pdf version template

More information

Publication Efficiency at DSI FEM CULS An Application of the Data Envelopment Analysis

Publication Efficiency at DSI FEM CULS An Application of the Data Envelopment Analysis Publication Efficiency at DSI FEM CULS An Alication of the Data Enveloment Analysis Martin Flégl, Helena Brožová 1 Abstract. The education and research efficiency at universities has always been very imortant

More information

PRE-CALCULUS SUMMER PACKET IINTRODUCTION 12-3

PRE-CALCULUS SUMMER PACKET IINTRODUCTION 12-3 NAME PRE-CALCULUS SUMMER PACKET IINTRODUCTION 12-3 This packet is due on the first day of school in September. You are responsible to do and show work for any 50 problems that you decide to do. You must

More information

MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question.

MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question. AP Stats: Test Review - Chapters 16-17 Name Period MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question. Find the expected value of the random variable.

More information

Matching Markets and Social Networks

Matching Markets and Social Networks Matching Markets and Social Networks Tilman Klum Emory University Mary Schroeder University of Iowa Setember 0 Abstract We consider a satial two-sided matching market with a network friction, where exchange

More information

Homework #5 7 th week Math 240 Thursday October 24, 2013

Homework #5 7 th week Math 240 Thursday October 24, 2013 . Let a, b > be integers and g : = gcd(a, b) its greatest common divisor. Show that if a = g q a and b = g q b then q a and q b are relatively rime. Since gcd(κ a, κ b) = κ gcd(a, b) in articular, for

More information

3 Ways to Write Ratios

3 Ways to Write Ratios RATIO & PROPORTION Sec 1. Defining Ratio & Proportion A RATIO is a comparison between two quantities. We use ratios every day; one Pepsi costs 50 cents describes a ratio. On a map, the legend might tell

More information

Yao s Minimax Principle

Yao s Minimax Principle Complexity of algorithms The complexity of an algorithm is usually measured with respect to the size of the input, where size may for example refer to the length of a binary word describing the input,

More information

Midterm Exam: Tuesday 28 March in class Sample exam problems ( Homework 5 ) available tomorrow at the latest

Midterm Exam: Tuesday 28 March in class Sample exam problems ( Homework 5 ) available tomorrow at the latest Plan Martingales 1. Basic Definitions 2. Examles 3. Overview of Results Reading: G&S Section 12.1-12.4 Next Time: More Martingales Midterm Exam: Tuesday 28 March in class Samle exam roblems ( Homework

More information

MATH 218 FINAL EXAMINATION December 17, 2003 Professors: J. Colwell, F. Lin, K. Styrkas, E. Verona, Z. Vorel.

MATH 218 FINAL EXAMINATION December 17, 2003 Professors: J. Colwell, F. Lin, K. Styrkas, E. Verona, Z. Vorel. MATH 218 FINAL EXAMINATION December 17, 2003 Professors: J. Colwell, F. Lin, K. Styrkas, E. Verona, Z. Vorel. Problem 1. A random sample of 50 purchases at a department store produced the following contingency

More information

Chapter 4 and 5 Note Guide: Probability Distributions

Chapter 4 and 5 Note Guide: Probability Distributions Chapter 4 and 5 Note Guide: Probability Distributions Probability Distributions for a Discrete Random Variable A discrete probability distribution function has two characteristics: Each probability is

More information

Statistics Chapter 8

Statistics Chapter 8 Statistics Chapter 8 Binomial & Geometric Distributions Time: 1.5 + weeks Activity: A Gaggle of Girls The Ferrells have 3 children: Jennifer, Jessica, and Jaclyn. If we assume that a couple is equally

More information

A random variable X is a function that assigns (real) numbers to the elements of the sample space S of a random experiment.

A random variable X is a function that assigns (real) numbers to the elements of the sample space S of a random experiment. RANDOM VARIABLES and PROBABILITY DISTRIBUTIONS A random variable X is a function that assigns (real) numbers to the elements of the samle sace S of a random exeriment. The value sace V of a random variable

More information

Price Gap and Welfare

Price Gap and Welfare APPENDIX D Price Ga and Welfare Derivation of the Price-Ga Formula This aendix details the derivation of the rice-ga formula (see chaters 2 and 5) under two assumtions: (1) the simlest case, where there

More information

EXERCISES ACTIVITY 6.7

EXERCISES ACTIVITY 6.7 762 CHAPTER 6 PROBABILITY MODELS EXERCISES ACTIVITY 6.7 1. Compute each of the following: 100! a. 5! I). 98! c. 9P 9 ~~ d. np 9 g- 8Q e. 10^4 6^4 " 285^1 f-, 2 c 5 ' sq ' sq 2. How many different ways

More information

Asymptotic Notation. Instructor: Laszlo Babai June 14, 2002

Asymptotic Notation. Instructor: Laszlo Babai June 14, 2002 Asymptotic Notation Instructor: Laszlo Babai June 14, 2002 1 Preliminaries Notation: exp(x) = e x. Throughout this course we shall use the following shorthand in quantifier notation. ( a) is read as for

More information

(c) The probability that a randomly selected driver having a California drivers license

(c) The probability that a randomly selected driver having a California drivers license Statistics Test 2 Name: KEY 1 Classify each statement as an example of classical probability, empirical probability, or subjective probability (a An executive for the Krusty-O cereal factory makes an educated

More information

( ) ( ) β. max. subject to. ( ) β. x S

( ) ( ) β. max. subject to. ( ) β. x S Intermediate Microeconomic Theory: ECON 5: Alication of Consumer Theory Constrained Maimization In the last set of notes, and based on our earlier discussion, we said that we can characterize individual

More information

Other Types of Distributions

Other Types of Distributions Other Types of Distributions Unit 9 Probability Distributions Warm Up! The chance that a U.S. police chief believes the death penalty significantly reduces the number of homicides is 1 in 4. If a random

More information

Math 167: Mathematical Game Theory Instructor: Alpár R. Mészáros

Math 167: Mathematical Game Theory Instructor: Alpár R. Mészáros Math 167: Mathematical Game Theory Instructor: Alpár R. Mészáros Midterm #1, February 3, 2017 Name (use a pen): Student ID (use a pen): Signature (use a pen): Rules: Duration of the exam: 50 minutes. By

More information

Confidence Intervals for a Proportion Using Inverse Sampling when the Data is Subject to False-positive Misclassification

Confidence Intervals for a Proportion Using Inverse Sampling when the Data is Subject to False-positive Misclassification Journal of Data Science 13(015), 63-636 Confidence Intervals for a Proortion Using Inverse Samling when the Data is Subject to False-ositive Misclassification Kent Riggs 1 1 Deartment of Mathematics and

More information

4.2 Bernoulli Trials and Binomial Distributions

4.2 Bernoulli Trials and Binomial Distributions Arkansas Tech University MATH 3513: Applied Statistics I Dr. Marcel B. Finan 4.2 Bernoulli Trials and Binomial Distributions A Bernoulli trial 1 is an experiment with exactly two outcomes: Success and

More information

Record on a ScanTron, your choosen response for each question. You may write on this form. One page of notes and a calculator are allowed.

Record on a ScanTron, your choosen response for each question. You may write on this form. One page of notes and a calculator are allowed. Ch 16, 17 Math 240 Exam 4 v1 Good SAMPLE No Book, Yes 1 Page Notes, Yes Calculator, 120 Minutes Dressler Record on a ScanTron, your choosen response for each question. You may write on this form. One page

More information

Total number of balls played

Total number of balls played Class IX - NCERT Maths Exercise (15.1) Question 1: In a cricket math, a batswoman hits a boundary 6 times out of 30 balls she plays. Find the probability that she did not hit a boundary. Solution 1: Number

More information

MAT121: Mathematics for Business and Information Science Final Exam Review Packet

MAT121: Mathematics for Business and Information Science Final Exam Review Packet MAT121: Mathematics for Business and Information Science Final Exam Review Packet A. Calculate the exact distance (i.e., simplified radicals where appropriate, not decimal approximations using a calculator)

More information

A useful modeling tricks.

A useful modeling tricks. .7 Joint models for more than two outcomes We saw that we could write joint models for a pair of variables by specifying the joint probabilities over all pairs of outcomes. In principal, we could do this

More information

1. Find the slope and y-intercept for

1. Find the slope and y-intercept for MA 0 REVIEW PROBLEMS FOR THE FINAL EXAM This review is to accompany the course text which is Finite Mathematics for Business, Economics, Life Sciences, and Social Sciences, th Edition by Barnett, Ziegler,

More information

Ratios, Rates, and Conversions. Section 4-1 Part 1

Ratios, Rates, and Conversions. Section 4-1 Part 1 Ratios, Rates, and Conversions Section 4-1 Part 1 Vocabulary Ratio Rate Unit Rate Conversion Factor Unit Analysis Definition Ratio is a comparison of two quantities by division. The ratio of a to b can

More information

Homework Problems In each of the following situations, X is a count. Does X have a binomial distribution? Explain. 1. You observe the gender of the next 40 children born in a hospital. X is the number

More information

Week 3: Binomials Coefficients. 26 & 28 September MA204/MA284 : Discrete Mathematics. Niall Madden (and Emil Sköldberg)

Week 3: Binomials Coefficients. 26 & 28 September MA204/MA284 : Discrete Mathematics. Niall Madden (and Emil Sköldberg) (1/22) qz0z0z0z LNZ0Z0Z0 0mkZ0Z0Z Z0Z0Z0Z0 0Z0Z0Z0Z Z0Z0Z0Z0 0Z0Z0Z0Z Z0Z0Z0Z0 pz0z0z0z OpO0Z0Z0 0ZKZ0Z0Z Z0Z0Z0Z0 0Z0Z0Z0Z Z0Z0Z0Z0 0Z0Z0Z0Z Z0Z0Z0Z0 MA204/MA284 : Discrete Mathematics Week 3: Binomials

More information

CSE 21 Winter 2016 Homework 6 Due: Wednesday, May 11, 2016 at 11:59pm. Instructions

CSE 21 Winter 2016 Homework 6 Due: Wednesday, May 11, 2016 at 11:59pm. Instructions CSE 1 Winter 016 Homework 6 Due: Wednesday, May 11, 016 at 11:59pm Instructions Homework should be done in groups of one to three people. You are free to change group members at any time throughout the

More information

4.1 Probability Distributions

4.1 Probability Distributions Probability and Statistics Mrs. Leahy Chapter 4: Discrete Probability Distribution ALWAYS KEEP IN MIND: The Probability of an event is ALWAYS between: and!!!! 4.1 Probability Distributions Random Variables

More information

Chapter 5. Discrete Probability Distributions. McGraw-Hill, Bluman, 7 th ed, Chapter 5 1

Chapter 5. Discrete Probability Distributions. McGraw-Hill, Bluman, 7 th ed, Chapter 5 1 Chapter 5 Discrete Probability Distributions McGraw-Hill, Bluman, 7 th ed, Chapter 5 1 Chapter 5 Overview Introduction 5-1 Probability Distributions 5-2 Mean, Variance, Standard Deviation, and Expectation

More information

Oliver Hinz. Il-Horn Hann

Oliver Hinz. Il-Horn Hann REEARCH ARTICLE PRICE DICRIMINATION IN E-COMMERCE? AN EXAMINATION OF DYNAMIC PRICING IN NAME-YOUR-OWN PRICE MARKET Oliver Hinz Faculty of Economics and usiness Administration, Goethe-University of Frankfurt,

More information

Summary of the Chief Features of Alternative Asset Pricing Theories

Summary of the Chief Features of Alternative Asset Pricing Theories Summary o the Chie Features o Alternative Asset Pricing Theories CAP and its extensions The undamental equation o CAP ertains to the exected rate o return time eriod into the uture o any security r r β

More information

MATH 205 HOMEWORK #1 OFFICIAL SOLUTION

MATH 205 HOMEWORK #1 OFFICIAL SOLUTION MATH 205 HOMEWORK #1 OFFICIAL SOLUTION Problem 2: Show that if there exists a ijective field homomorhism F F the char F = char F. Solutio: Let ϕ be the homomorhism, suose that char F =. Note that ϕ(1 =

More information

Discrete Probability Distributions

Discrete Probability Distributions Discrete Probability Distributions Chapter 6 Learning Objectives Define terms random variable and probability distribution. Distinguish between discrete and continuous probability distributions. Calculate

More information

3.1 Properties of Binomial Coefficients

3.1 Properties of Binomial Coefficients 3 Properties of Binomial Coefficients 31 Properties of Binomial Coefficients Here is the famous recursive formula for binomial coefficients Lemma 31 For 1 < n, 1 1 ( n 1 ) This equation can be proven by

More information

the number of correct answers on question i. (Note that the only possible values of X i

the number of correct answers on question i. (Note that the only possible values of X i 6851_ch08_137_153 16/9/02 19:48 Page 137 8 8.1 (a) No: There is no fixed n (i.e., there is no definite upper limit on the number of defects). (b) Yes: It is reasonable to believe that all responses are

More information

What is the probability of success? Failure? How could we do this simulation using a random number table?

What is the probability of success? Failure? How could we do this simulation using a random number table? Probability Ch.4, sections 4.2 & 4.3 Binomial and Geometric Distributions Name: Date: Pd: 4.2. What is a binomial distribution? How do we find the probability of success? Suppose you have three daughters.

More information

Iterated Dominance and Nash Equilibrium

Iterated Dominance and Nash Equilibrium Chapter 11 Iterated Dominance and Nash Equilibrium In the previous chapter we examined simultaneous move games in which each player had a dominant strategy; the Prisoner s Dilemma game was one example.

More information

Asymmetric Information

Asymmetric Information Asymmetric Information Econ 235, Sring 2013 1 Wilson [1980] What haens when you have adverse selection? What is an equilibrium? What are we assuming when we define equilibrium in one of the ossible ways?

More information

MATH 227 CP 6 SHORT ANSWER. Write the word or phrase that best completes each statement or answers the question.

MATH 227 CP 6 SHORT ANSWER. Write the word or phrase that best completes each statement or answers the question. MATH 227 CP 6 SHORT ANSWER. Write the word or phrase that best completes each statement or answers the question. Identify the given random variable as being discrete or continuous. 1) The number of phone

More information

Chapter 3. Lecture 3 Sections

Chapter 3. Lecture 3 Sections Chapter 3 Lecture 3 Sections 3.4 3.5 Measure of Position We would like to compare values from different data sets. We will introduce a z score or standard score. This measures how many standard deviation

More information

The Kelly Criterion. How To Manage Your Money When You Have an Edge

The Kelly Criterion. How To Manage Your Money When You Have an Edge The Kelly Criterion How To Manage Your Money When You Have an Edge The First Model You play a sequence of games If you win a game, you win W dollars for each dollar bet If you lose, you lose your bet For

More information

1. Variability in estimates and CLT

1. Variability in estimates and CLT Unit3: Foundationsforinference 1. Variability in estimates and CLT Sta 101 - Fall 2015 Duke University, Department of Statistical Science Dr. Çetinkaya-Rundel Slides posted at http://bit.ly/sta101_f15

More information

H.S.E. PREP SEC

H.S.E. PREP SEC H.S.E. PREP COURSE @ SEC VERSION 2.0, 2018 MODULE B RATIONALS STUDENT WORKBOOK H.S.E. PREP COURSE MODULE B: RATIONALS CONTENTS REVIEW... 3 OPERATIONS WITH INTERGERS... 3 DECIMALS... 4 BASICS... 4 ADDING

More information