CSC/MTH 231 Discrete Structures II Spring, Homework 5


 Rafe Watts
 4 years ago
 Views:
Transcription
1 CSC/MTH 231 Discrete Structures II Spring, 2010 Homework 5 Name 1. A six sided die D (with sides numbered 1, 2, 3, 4, 5, 6) is thrown once. a. What is the probability that a 3 is thrown? b. What is the probability that a 7 is thrown? 2. A six sided die D (with sides numbered 1, 2, 3, 4, 5, 6) is thrown twice and each time the value thrown is recorded. a. How many trials are performed? b. What is S, the set of possible outcomes for each trial (i.e. on one single throw of one die)? c. What is S (i.e. the number of different possible outcomes) for each trial? d. If E 1 is the event that 3 the number thrown on any one trial, what is E 1 (i.e. how many different outcomes cause event E 1 to occur)? e. What is the probability on any given trial that event E 1 occurs? f. What is the probability that E 1, the complimentary event of E 1, occurs? g. If E 2 is the event that the number thrown is odd, what is the probability on any given trial that Event E 2 occurs? h. What is the probability the event E 2 occurs twice in a row (i.e. on the first trial and the second trial)? i. What is the probability on any given trial that events E 1 and E 2 both occur? j. What is the probability on any given trial that either event E 1 or event E 2 occurs? k. What is the probability that the sum of the number thrown on the first trial and the number thrown on the second trial = 6?
2 3. Exercise Set 6.1 (page 399) # 16 What is the probability that a 5card poker hand contains a flush? # 20 What is the probability that a 5card poker hand contains a royal flush (i.e. AKQJ10 of the same suit)? # 24A Find the probability of winning the lottery by selecting the correct 6 integers, where order does not matter, from the positive integers # 28 In a super lottery a player selects 7 numbers out of the first 80 positive integers. What is the probability that a person wins the grand prize by picking 7 numbers that are among the 11 numbers selected at random by a computer? # 38 Two events E 1 and E 2 are call independent if p(e 1 E 2 ) = p(e1) * p(e 2 ). For each of the following pairs of events, which are subsets of the set of all possible outcomes when a coin is tossed 3 times, determine whether or not they are independent. a) E 1 : the first coin comes up tails; E 2 : the second coin comes up heads b) E 1 : the first coin comes up tails; E 2 : two, and not three, heads come up in a row c) E 1 : the second coin comes up tails; E 2 : two, and not three, heads come up in a row
3 4. Look at problem 35 on page 399. Its answers are in the back of the book. Then fill in the blanks and answer the questions below. Event E = winning on a trial (i.e. a spin) A particular casino pays you double the amount that you bet if you bet that red will come up and it does. (That is, if you bet $1 on RED and the wheel does land on a RED number, you will get $2 back, your original $1 plus another $1.) P(E) = that you win $1 & P(E ) = that you lose $1. It pays you 6 times your bet if you bet that the wheel will land on one of the numbers between 1 and 6 inclusive, and it does. (If you bet $1, you will get $6 back, your original $1 plus another $5.) P(E) = that you win $5 & P(E ) = that you lose $1. It pays you 36 times your bet if you bet that the wheel will land on a specific number (say 14) and it does. (If you bet $1, you will get $36 back, your original $1 plus another $35.) P(E) = that you win $35 & P(E ) = that you lose $1. a. Which of these 3 options gives you the greatest probability of winning at least something on any given spin? b. Which of these 3 options gives you the most money back on a spin of the wheel, relative to the probability of winning on that spin, or are they all the same? c. What is the probability that the "house" wins on any given spin? d. Over the course of a night, with hundreds of people playing roulette, how much does the house win, on average, for every dollar bet?
4 5. Variation on the Monty Hall "door" puzzle introduced on page 398. There are 5 doors. One has a great prize behind it and 4 have nothing behind them. You pick a door. (Let's call it door 'A'.) Then the host randomly eliminates 2 of the other 4 doors that have nothing behind them. (Let's call them doors 'D' and 'E'.) So there is now the door you selected ('A') and two other doors ('B' and 'C'). You are now given the choice of sticking with the door you originally chose or picking a different door from the remaining doors. a. What should you do? b. What is the probability you have picked the winning door if you stay with door 'A'? c. What is the probability of winning if you change your selection and pick either door 'B' or door 'C' instead? 6. Exercise set 6.1 Problem # 41 (page 400). The answers are in the back of the book, but you must show your work to indicate how you arrive at the correct answer. This is the last problem in the section. It has 3 parts (a,b,c) and begins "This problem was posed by the Chevalier de Mere ")
5 7. Exercise set 6.2 (pages ) a. # 16 Show that if E and F are independent events, then E' and F' are also independent events. b. # 18a What is the probability that 2 people chosen at random were born on the same day of the week? c. # 26 Let E be the event that a randomly generated bit string (i.e. made up of 0s and 1s) of length 3 contains an odd number of 1s and F be the event that the string starts with 1. Are E and F independent? Show why or why not. d. # 28 Assume that the probability a child is a boy is 0.51 and that the sexes of children born into a family are independent. What is the probability that a family of 5 children has: a) exactly 3 boys b) at least 1 boy c) at least 1 girl d) all children of the same sex e. # 34 Find each of the following probabilities when n independent Bernoulli trials are carried out with a probability of success p. a) the probability of no successes b) the probability of at least one success c) the probability of at most one success d) the probability of at least 2 successes
6 8. Exercise set 6.3 (page 424) a. # 2 Suppose that E and F are events in a sample space and p(e) = 2/3, p(f) = 3/4, and p(f E) = 5/8. Find p(e F) b. # 4 This is the problem that begins "Suppose that Ann selects a ball ". c. # 6 This is the problem that begins "When a test for steroids is given to soccer players ".
7 Where possible, show your work as well as the answer. 9. Exercise set 6.4 (pages ) a. # 2 What is the expected number of heads that come up when a fair coin is flipped 10 times? Mapping of random variable f(s) s f(s) tails 0 average number of heads = heads 1 b. # 4 A coin is biased so that the probability a head comes up when it is flipped is 0.6. What is the expected number of heads that come up when it is flipped 10 times? average number of heads = c. # 8 What is the expected sum of the numbers that appear when 3 fair dice are rolled? d. # 12b Suppose we roll a die until a 6 comes up. (not required) What is the probability that we roll the die n times? What is the expected number of times we roll the dice? (Hint: Use a geometric distribution.) 10. A random variable X maps outcomes in a sample space S to the following values with the probabilities shown here /8 2/8 3/8 1/8 1/8 a. What is the mean value (i.e. average or expected value) of X? b. What is the variance of X? c. What is the standard deviation of X?
8 11. Chapter 6 Supplementary Exercises (page 443) # 6 A dodecahedral die has 12 faces numbered a. What is the expected value of the number that comes up when a fair dodecahedral die is rolled. (i.e. the average value from a set of rolls) b. What is the variance of the number that comes up when a fair dodecahedral die is rolled? (i.e. the variance of the observed average value rolled from the expected average)
Section 6.1 #16. Question: What is the probability that a fivecard poker hand contains a flush, that is, five cards of the same suit?
Section 6.1 #16 What is the probability that a fivecard poker hand contains a flush, that is, five cards of the same suit? page 1 Section 6.1 #38 Two events E 1 and E 2 are called independent if p(e 1
More informationJunior Circle Meeting 5 Probability. May 2, ii. In an actual experiment, can one get a different number of heads when flipping a coin 100 times?
Junior Circle Meeting 5 Probability May 2, 2010 1. We have a standard coin with one side that we call heads (H) and one side that we call tails (T). a. Let s say that we flip this coin 100 times. i. How
More informationRosen, Discrete Mathematics and Its Applications, 6th edition Extra Examples
Rosen, Discrete Mathematics and Its Applications, 6th edition Extra Examples Section 6.1 An Introduction to Discrete Probability Page references correspond to locations of Extra Examples icons in the textbook.
More informationSection Summary. Finite Probability Probabilities of Complements and Unions of Events Probabilistic Reasoning
Section 7.1 Section Summary Finite Probability Probabilities of Complements and Unions of Events Probabilistic Reasoning Probability of an Event PierreSimon Laplace (17491827) We first study PierreSimon
More informationDiscrete Structures for Computer Science
Discrete Structures for Computer Science William Garrison bill@cs.pitt.edu 6311 Sennott Square Lecture #23: Discrete Probability Based on materials developed by Dr. Adam Lee The study of probability is
More informationProbability MAT230. Fall Discrete Mathematics. MAT230 (Discrete Math) Probability Fall / 37
Probability MAT230 Discrete Mathematics Fall 2018 MAT230 (Discrete Math) Probability Fall 2018 1 / 37 Outline 1 Discrete Probability 2 Sum and Product Rules for Probability 3 Expected Value MAT230 (Discrete
More informationMATH 215 DISCRETE MATHEMATICS INSTRUCTOR: P. WENG
MATH DISCRETE MATHEMATICS INSTRUCTOR: P. WENG Counting and Probability Suggested Problems Basic Counting Skills, InclusionExclusion, and Complement. (a An office building contains 7 floors and has 7 offices
More informationThe study of probability is concerned with the likelihood of events occurring. Many situations can be analyzed using a simplified model of probability
The study of probability is concerned with the likelihood of events occurring Like combinatorics, the origins of probability theory can be traced back to the study of gambling games Still a popular branch
More information1. A factory makes calculators. Over a long period, 2 % of them are found to be faulty. A random sample of 100 calculators is tested.
1. A factory makes calculators. Over a long period, 2 % of them are found to be faulty. A random sample of 0 calculators is tested. Write down the expected number of faulty calculators in the sample. Find
More informationRandom Variables. A Random Variable is a rule that assigns a number to each outcome of an experiment.
Random Variables When we perform an experiment, we are often interested in recording various pieces of numerical data for each trial. For example, when a patient visits the doctor s office, their height,
More information, x {1, 2, k}, where k > 0. (a) Write down P(X = 2). (1) (b) Show that k = 3. (4) Find E(X). (2) (Total 7 marks)
1. The probability distribution of a discrete random variable X is given by 2 x P(X = x) = 14, x {1, 2, k}, where k > 0. Write down P(X = 2). (1) Show that k = 3. Find E(X). (Total 7 marks) 2. In a game
More informationEx 1: A coin is flipped. Heads, you win $1. Tails, you lose $1. What is the expected value of this game?
AFM Unit 7 Day 5 Notes Expected Value and Fairness Name Date Expected Value: the weighted average of possible values of a random variable, with weights given by their respective theoretical probabilities.
More informationRandom Variables. Outcome X (1, 1) 2 (2, 1) 3 (3, 1) 4 (4, 1) 5. (6, 1) (6, 2) (6, 3) (6, 4) (6, 5) (6, 6) }
Random Variables When we perform an experiment, we are often interested in recording various pieces of numerical data for each trial. For example, when a patient visits the doctor s office, their height,
More informationDiscrete Random Variables Day 1
Discrete Random Variables Day 1 What is a Random Variable? Every probability problem is equivalent to drawing something from a bag (perhaps more than once) Like Flipping a coin 3 times is equivalent to
More informationThe Teachers Circle Mar. 20, 2012 HOW TO GAMBLE IF YOU MUST (I ll bet you $5 that if you give me $10, I ll give you $20.)
The Teachers Circle Mar. 2, 22 HOW TO GAMBLE IF YOU MUST (I ll bet you $ that if you give me $, I ll give you $2.) Instructor: Paul Zeitz (zeitzp@usfca.edu) Basic Laws and Definitions of Probability If
More informationProbability. Dr. Zhang Fordham Univ.
Probability! Dr. Zhang Fordham Univ. 1 Probability: outline Introduction! Experiment, event, sample space! Probability of events! Calculate Probability! Through counting! Sum rule and general sum rule!
More informationUnit 9: Probability Assignments
Unit 9: Probability Assignments #1: Basic Probability In each of exercises 1 & 2, find the probability that the spinner shown would land on (a) red, (b) yellow, (c) blue. 1. 2. Y B B Y B R Y Y B R 3. Suppose
More information4.1 Sample Spaces and Events
4.1 Sample Spaces and Events An experiment is an activity that has observable results. Examples: Tossing a coin, rolling dice, picking marbles out of a jar, etc. The result of an experiment is called an
More informationHere are two situations involving chance:
Obstacle Courses 1. Introduction. Here are two situations involving chance: (i) Someone rolls a die three times. (People usually roll dice in pairs, so dice is more common than die, the singular form.)
More informationCounting and Probability
Counting and Probability Lecture 42 Section 9.1 Robb T. Koether HampdenSydney College Wed, Apr 9, 2014 Robb T. Koether (HampdenSydney College) Counting and Probability Wed, Apr 9, 2014 1 / 17 1 Probability
More informationDue Friday February 17th before noon in the TA drop box, basement, AP&M. HOMEWORK 3 : HAND IN ONLY QUESTIONS: 2, 4, 8, 11, 13, 15, 21, 24, 27
Exercise Sheet 3 jacques@ucsd.edu Due Friday February 17th before noon in the TA drop box, basement, AP&M. HOMEWORK 3 : HAND IN ONLY QUESTIONS: 2, 4, 8, 11, 13, 15, 21, 24, 27 1. A sixsided die is tossed.
More informationClass XII Chapter 13 Probability Maths. Exercise 13.1
Exercise 13.1 Question 1: Given that E and F are events such that P(E) = 0.6, P(F) = 0.3 and P(E F) = 0.2, find P (E F) and P(F E). It is given that P(E) = 0.6, P(F) = 0.3, and P(E F) = 0.2 Question 2:
More informationThe topic for the third and final major portion of the course is Probability. We will aim to make sense of statements such as the following:
CS 70 Discrete Mathematics for CS Spring 2006 Vazirani Lecture 17 Introduction to Probability The topic for the third and final major portion of the course is Probability. We will aim to make sense of
More informationChapter 7 Homework Problems. 1. If a carefully made die is rolled once, it is reasonable to assign probability 1/6 to each of the six faces.
Chapter 7 Homework Problems 1. If a carefully made die is rolled once, it is reasonable to assign probability 1/6 to each of the six faces. A. What is the probability of rolling a number less than 3. B.
More informationSTATION 1: ROULETTE. Name of Guesser Tally of Wins Tally of Losses # of Wins #1 #2
Casino Lab 2017  ICM The House Always Wins! Casinos rely on the laws of probability and expected values of random variables to guarantee them profits on a daily basis. Some individuals will walk away
More informationProbability Rules. 2) The probability, P, of any event ranges from which of the following?
Name: WORKSHEET : Date: Answer the following questions. 1) Probability of event E occurring is... P(E) = Number of ways to get E/Total number of outcomes possible in S, the sample space....if. 2) The probability,
More informationCasino Lab AP Statistics
Casino Lab AP Statistics Casino games are governed by the laws of probability (and those enacted by politicians, too). The same laws (probabilistic, not political) rule the entire known universe. If the
More informationDiscrete Mathematics and Probability Theory Spring 2016 Rao and Walrand Note 13
CS 70 Discrete Mathematics and Probability Theory Spring 2016 Rao and Walrand Note 13 Introduction to Discrete Probability In the last note we considered the probabilistic experiment where we flipped a
More information1. An office building contains 27 floors and has 37 offices on each floor. How many offices are in the building?
1. An office building contains 27 floors and has 37 offices on each floor. How many offices are in the building? 2. A particular brand of shirt comes in 12 colors, has a male version and a female version,
More information6. a) Determine the probability distribution. b) Determine the expected sum of two dice. c) Repeat parts a) and b) for the sum of
d) generating a random number between 1 and 20 with a calculator e) guessing a person s age f) cutting a card from a wellshuffled deck g) rolling a number with two dice 3. Given the following probability
More information1. The chance of getting a flush in a 5card poker hand is about 2 in 1000.
CS 70 Discrete Mathematics for CS Spring 2008 David Wagner Note 15 Introduction to Discrete Probability Probability theory has its origins in gambling analyzing card games, dice, roulette wheels. Today
More informationOutcome X (1, 1) 2 (2, 1) 3 (3, 1) 4 (4, 1) 5 {(1, 1) (1, 2) (1, 3) (1, 4) (1, 5) (1, 6) (6, 1) (6, 2) (6, 3) (6, 4) (6, 5) (6, 6)}
Section 8: Random Variables and probability distributions of discrete random variables In the previous sections we saw that when we have numerical data, we can calculate descriptive statistics such as
More informationElementary Statistics. Basic Probability & Odds
Basic Probability & Odds What is a Probability? Probability is a branch of mathematics that deals with calculating the likelihood of a given event to happen or not, which is expressed as a number between
More informationProbability and the Monty Hall Problem Rong Huang January 10, 2016
Probability and the Monty Hall Problem Rong Huang January 10, 2016 Warmup: There is a sequence of number: 1, 2, 4, 8, 16, 32, 64, How does this sequence work? How do you get the next number from the previous
More informationProbability. Ms. Weinstein Probability & Statistics
Probability Ms. Weinstein Probability & Statistics Definitions Sample Space The sample space, S, of a random phenomenon is the set of all possible outcomes. Event An event is a set of outcomes of a random
More informationDISCUSSION #8 FRIDAY MAY 25 TH Sophie Engle (Teacher Assistant) ECS20: Discrete Mathematics
DISCUSSION #8 FRIDAY MAY 25 TH 2007 Sophie Engle (Teacher Assistant) ECS20: Discrete Mathematics 2 Homework 8 Hints and Examples 3 Section 5.4 Binomial Coefficients Binomial Theorem 4 Example: j j n n
More informationMath 1313 Section 6.2 Definition of Probability
Math 1313 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
More informationThe next several lectures will be concerned with probability theory. We will aim to make sense of statements such as the following:
CS 70 Discrete Mathematics for CS Fall 2004 Rao Lecture 14 Introduction to Probability The next several lectures will be concerned with probability theory. We will aim to make sense of statements such
More informationProbability of Independent and Dependent Events
706 Practice A Probability of In and ependent Events ecide whether each set of events is or. Explain your answer.. A student spins a spinner and rolls a number cube.. A student picks a raffle ticket from
More informationIndependent Events. 1. Given that the second baby is a girl, what is the. e.g. 2 The probability of bearing a boy baby is 2
Independent Events 7. Introduction Consider the following examples e.g. E throw a die twice A first thrown is "" second thrown is "" o find P( A) Solution: Since the occurrence of Udoes not dependu on
More informationMAT104: Fundamentals of Mathematics II Summary of Counting Techniques and Probability. Preliminary Concepts, Formulas, and Terminology
MAT104: Fundamentals of Mathematics II Summary of Counting Techniques and Probability Preliminary Concepts, Formulas, and Terminology Meanings of Basic Arithmetic Operations in Mathematics Addition: Generally
More informationProbability Paradoxes
Probability Paradoxes Washington University Math Circle February 20, 2011 1 Introduction We re all familiar with the idea of probability, even if we haven t studied it. That is what makes probability so
More informationSection The Multiplication Principle and Permutations
Section 2.1  The Multiplication Principle and Permutations Example 1: A yogurt shop has 4 flavors (chocolate, vanilla, strawberry, and blueberry) and three sizes (small, medium, and large). How many different
More information7.1 Experiments, Sample Spaces, and Events
7.1 Experiments, Sample Spaces, and Events An experiment is an activity that has observable results. Examples: Tossing a coin, rolling dice, picking marbles out of a jar, etc. The result of an experiment
More informationProbability and Counting Techniques
Probability and Counting Techniques Diana Pell (Multiplication Principle) Suppose that a task consists of t choices performed consecutively. Suppose that choice 1 can be performed in m 1 ways; for each
More informationLesson 4: Calculating Probabilities for Chance Experiments with Equally Likely Outcomes
NYS COMMON CORE MAEMAICS CURRICULUM 7 : Calculating Probabilities for Chance Experiments with Equally Likely Classwork Examples: heoretical Probability In a previous lesson, you saw that to find an estimate
More informationContemporary Mathematics Math 1030 Sample Exam I Chapters Time Limit: 90 Minutes No Scratch Paper Calculator Allowed: Scientific
Contemporary Mathematics Math 1030 Sample Exam I Chapters 1315 Time Limit: 90 Minutes No Scratch Paper Calculator Allowed: Scientific Name: The point value of each problem is in the lefthand margin.
More informationThe point value of each problem is in the lefthand margin. You must show your work to receive any credit, except on problems 1 & 2. Work neatly.
Introduction to Statistics Math 1040 Sample Exam II Chapters 57 4 Problem Pages 4 Formula/Table Pages Time Limit: 90 Minutes 1 No Scratch Paper Calculator Allowed: Scientific Name: The point value of
More informationCS1802 Week 9: Probability, Expectation, Entropy
CS02 Discrete Structures Recitation Fall 207 October 30  November 3, 207 CS02 Week 9: Probability, Expectation, Entropy Simple Probabilities i. What is the probability that if a die is rolled five times,
More informationLesson 4: Calculating Probabilities for Chance Experiments with Equally Likely Outcomes
Lesson : Calculating Probabilities for Chance Experiments with Equally Likely Outcomes Classwork Example : heoretical Probability In a previous lesson, you saw that to find an estimate of the probability
More informationNovember 11, Chapter 8: Probability: The Mathematics of Chance
Chapter 8: Probability: The Mathematics of Chance November 11, 2013 Last Time Probability Models and Rules Discrete Probability Models Equally Likely Outcomes Probability Rules Probability Rules Rule 1.
More information2 A fair coin is flipped 8 times. What is the probability of getting more heads than tails? A. 1 2 B E. NOTA
For all questions, answer E. "NOTA" means none of the above answers is correct. Calculator use NO calculators will be permitted on any test other than the Statistics topic test. The word "deck" refers
More informationWeek 1: Probability models and counting
Week 1: Probability models and counting Part 1: Probability model Probability theory is the mathematical toolbox to describe phenomena or experiments where randomness occur. To have a probability model
More informationPart 1: I can express probability as a fraction, decimal, and percent
Name: Pattern: Part 1: I can express probability as a fraction, decimal, and percent For #1 to #4, state the probability of each outcome. Write each answer as a) a fraction b) a decimal c) a percent Example:
More informationReview Questions on Ch4 and Ch5
Review Questions on Ch4 and Ch5 1. Find the mean of the distribution shown. x 1 2 P(x) 0.40 0.60 A) 1.60 B) 0.87 C) 1.33 D) 1.09 2. A married couple has three children, find the probability they are all
More informationI. WHAT IS PROBABILITY?
C HAPTER 3 PROAILITY Random Experiments I. WHAT IS PROAILITY? The weatherman on 10 o clock news program states that there is a 20% chance that it will snow tomorrow, a 65% chance that it will rain and
More informationPage 1 of 22. Website: Mobile:
Exercise 15.1 Question 1: Complete the following statements: (i) Probability of an event E + Probability of the event not E =. (ii) The probability of an event that cannot happen is. Such as event is called.
More informationName. Is the game fair or not? Prove your answer with math. If the game is fair, play it 36 times and record the results.
Homework 5.1C You must complete table. Use math to decide if the game is fair or not. If Period the game is not fair, change the point system to make it fair. Game 1 Circle one: Fair or Not 2 six sided
More informationFoundations of Computing Discrete Mathematics Solutions to exercises for week 12
Foundations of Computing Discrete Mathematics Solutions to exercises for week 12 Agata Murawska (agmu@itu.dk) November 13, 2013 Exercise (6.1.2). A multiplechoice test contains 10 questions. There are
More informationEECS 203 Spring 2016 Lecture 15 Page 1 of 6
EECS 203 Spring 2016 Lecture 15 Page 1 of 6 Counting We ve been working on counting for the last two lectures. We re going to continue on counting and probability for about 1.5 more lectures (including
More informationThe game of poker. Gambling and probability. Poker probability: royal flush. Poker probability: four of a kind
The game of poker Gambling and probability CS231 Dianna Xu 1 You are given 5 cards (this is 5card stud poker) The goal is to obtain the best hand you can The possible poker hands are (in increasing order):
More informationCOUNTING AND PROBABILITY
CHAPTER 9 COUNTING AND PROBABILITY It s as easy as 1 2 3. That s the saying. And in certain ways, counting is easy. But other aspects of counting aren t so simple. Have you ever agreed to meet a friend
More informationTEST A CHAPTER 11, PROBABILITY
TEST A CHAPTER 11, PROBABILITY 1. Two fair dice are rolled. Find the probability that the sum turning up is 9, given that the first die turns up an even number. 2. Two fair dice are rolled. Find the probability
More informationMidterm 2 Practice Problems
Midterm 2 Practice Problems May 13, 2012 Note that these questions are not intended to form a practice exam. They don t necessarily cover all of the material, or weight the material as I would. They are
More informationThe student will explain and evaluate the financial impact and consequences of gambling.
What Are the Odds? Standard 12 The student will explain and evaluate the financial impact and consequences of gambling. Lesson Objectives Recognize gambling as a form of risk. Calculate the probabilities
More informationBellwork Write each fraction as a percent Evaluate P P C C 6
Bellwork 21915 Write each fraction as a percent. 1. 2. 3. 4. Evaluate. 5. 6 P 3 6. 5 P 2 7. 7 C 4 8. 8 C 6 1 Objectives Find the theoretical probability of an event. Find the experimental probability
More informationINDIAN STATISTICAL INSTITUTE
INDIAN STATISTICAL INSTITUTE B1/BVR Probability Home Assignment 1 200707 1. A poker hand means a set of five cards selected at random from usual deck of playing cards. (a) Find the probability that it
More informationExam III Review Problems
c Kathryn Bollinger and Benjamin Aurispa, November 10, 2011 1 Exam III Review Problems Fall 2011 Note: Not every topic is covered in this review. Please also take a look at the previous WeekinReviews
More informationSection : Combinations and Permutations
Section 11.111.2: Combinations and Permutations Diana Pell A construction crew has three members. A team of two must be chosen for a particular job. In how many ways can the team be chosen? How many words
More informationRaise your hand if you rode a bus within the past month. Record the number of raised hands.
166 CHAPTER 3 PROBABILITY TOPICS Raise your hand if you rode a bus within the past month. Record the number of raised hands. Raise your hand if you answered "yes" to BOTH of the first two questions. Record
More informationExercise Class XI Chapter 16 Probability Maths
Exercise 16.1 Question 1: Describe the sample space for the indicated experiment: A coin is tossed three times. A coin has two faces: head (H) and tail (T). When a coin is tossed three times, the total
More informationA Probability Work Sheet
A Probability Work Sheet October 19, 2006 Introduction: Rolling a Die Suppose Geoff is given a fair sixsided die, which he rolls. What are the chances he rolls a six? In order to solve this problem, we
More informationIntermediate Math Circles November 1, 2017 Probability I
Intermediate Math Circles November 1, 2017 Probability I Probability is the study of uncertain events or outcomes. Games of chance that involve rolling dice or dealing cards are one obvious area of application.
More informationHomework 8 (for lectures on 10/14,10/16)
Fall 2014 MTH122 Survey of Calculus and its Applications II Homework 8 (for lectures on 10/14,10/16) Yin Su 2014.10.16 Topics in this homework: Topic 1 Discrete random variables 1. Definition of random
More informationPROBABILITY Case of cards
WORKSHEET NO1 PROBABILITY Case of cards WORKSHEET NO2 Case of two die Case of coins WORKSHEET NO3 1) Fill in the blanks: A. The probability of an impossible event is B. The probability of a sure
More informationChapter 11: Probability and Counting Techniques
Chapter 11: Probability and Counting Techniques Diana Pell Section 11.3: Basic Concepts of Probability Definition 1. A sample space is a set of all possible outcomes of an experiment. Exercise 1. An experiment
More informationIndependence Is The Word
Problem 1 Simulating Independent Events Describe two different events that are independent. Describe two different events that are not independent. The probability of obtaining a tail with a coin toss
More informationPROBABILITY. 1. Introduction. Candidates should able to:
PROBABILITY Candidates should able to: evaluate probabilities in simple cases by means of enumeration of equiprobable elementary events (e.g for the total score when two fair dice are thrown), or by calculation
More information23 Applications of Probability to Combinatorics
November 17, 2017 23 Applications of Probability to Combinatorics William T. Trotter trotter@math.gatech.edu Foreword Disclaimer Many of our examples will deal with games of chance and the notion of gambling.
More informationStatistics 1040 Summer 2009 Exam III
Statistics 1040 Summer 2009 Exam III 1. For the following basic probability questions. Give the RULE used in the appropriate blank (BEFORE the question), for each of the following situations, using one
More informationIndependent Events B R Y
. Independent Events Lesson Objectives Understand independent events. Use the multiplication rule and the addition rule of probability to solve problems with independent events. Vocabulary independent
More informationSimulations. 1 The Concept
Simulations In this lab you ll learn how to create simulations to provide approximate answers to probability questions. We ll make use of a particular kind of structure, called a box model, that can be
More informationProbability 1. Name: Total Marks: 1. An unbiased spinner is shown below.
Probability 1 A collection of 91 Maths GCSE Sample and Specimen questions from AQA, OCR and PearsonEdexcel. Name: Total Marks: 1. An unbiased spinner is shown below. (a) Write a number to make each sentence
More informationSTANDARD COMPETENCY : 1. To use the statistics rules, the rules of counting, and the characteristic of probability in problem solving.
Worksheet 4 th Topic : PROBABILITY TIME : 4 X 45 minutes STANDARD COMPETENCY : 1. To use the statistics rules, the rules of counting, and the characteristic of probability in problem solving. BASIC COMPETENCY:
More informationBell Work. WarmUp Exercises. Two sixsided dice are rolled. Find the probability of each sum or 7
WarmUp Exercises Two sixsided dice are rolled. Find the probability of each sum. 1. 7 Bell Work 2. 5 or 7 3. You toss a coin 3 times. What is the probability of getting 3 heads? WarmUp Notes Exercises
More informationProbability: Terminology and Examples Spring January 1, / 22
Probability: Terminology and Examples 18.05 Spring 2014 January 1, 2017 1 / 22 Board Question Deck of 52 cards 13 ranks: 2, 3,..., 9, 10, J, Q, K, A 4 suits:,,,, Poker hands Consists of 5 cards A onepair
More informationMiniLecture 6.1 Discrete Random Variables
MiniLecture 6.1 Discrete Random Variables Objectives 1. Distinguish between discrete and continuous random variables 2. Identify discrete probability distributions 3. Construct probability histograms
More informationMath 147 Lecture Notes: Lecture 21
Math 147 Lecture Notes: Lecture 21 Walter Carlip March, 2018 The Probability of an Event is greater or less, according to the number of Chances by which it may happen, compared with the whole number of
More informationFoundations of Probability Worksheet Pascal
Foundations of Probability Worksheet Pascal The basis of probability theory can be traced back to a small set of major events that set the stage for the development of the field as a branch of mathematics.
More informationMathematical Foundations HW 5 By 11:59pm, 12 Dec, 2015
1 Probability Axioms Let A,B,C be three arbitrary events. Find the probability of exactly one of these events occuring. Sample space S: {ABC, AB, AC, BC, A, B, C, }, and S = 8. P(A or B or C) = 3 8. note:
More informationA. 15 B. 24 C. 45 D. 54
A spinner is divided into 8 equal sections. Lara spins the spinner 120 times. It lands on purple 30 times. How many more times does Lara need to spin the spinner and have it land on purple for the relative
More informationProbability. March 06, J. Boulton MDM 4U1. P(A) = n(a) n(s) Introductory Probability
Most people think they understand odds and probability. Do you? Decision 1: Pick a card Decision 2: Switch or don't Outcomes: Make a tree diagram Do you think you understand probability? Probability Write
More informationReview. Natural Numbers: Whole Numbers: Integers: Rational Numbers: Outline Sec Comparing Rational Numbers
FOUNDATIONS Outline Sec. 31 Gallo Name: Date: Review Natural Numbers: Whole Numbers: Integers: Rational Numbers: Comparing Rational Numbers Fractions: A way of representing a division of a whole into
More informationSuppose Y is a random variable with probability distribution function f(y). The mathematical expectation, or expected value, E(Y) is defined as:
Suppose Y is a random variable with probability distribution function f(y). The mathematical expectation, or expected value, E(Y) is defined as: E n ( Y) y f( ) µ i i y i The sum is taken over all values
More informationLesson 3: Chance Experiments with Equally Likely Outcomes
Lesson : Chance Experiments with Equally Likely Outcomes Classwork Example 1 Jamal, a 7 th grader, wants to design a game that involves tossing paper cups. Jamal tosses a paper cup five times and records
More informationName: Final Exam May 7, 2014
MATH 10120 Finite Mathematics Final Exam May 7, 2014 Name: Be sure that you have all 16 pages of the exam. The exam lasts for 2 hrs. There are 30 multiple choice questions, each worth 5 points. You may
More informationProbability with Set Operations. MATH 107: Finite Mathematics University of Louisville. March 17, Complicated Probability, 17th century style
Probability with Set Operations MATH 107: Finite Mathematics University of Louisville March 17, 2014 Complicated Probability, 17th century style 2 / 14 Antoine Gombaud, Chevalier de Méré, was fond of gambling
More information4.3 Rules of Probability
4.3 Rules of Probability If a probability distribution is not uniform, to find the probability of a given event, add up the probabilities of all the individual outcomes that make up the event. Example:
More information1. How many subsets are there for the set of cards in a standard playing card deck? How many subsets are there of size 8?
Math 1711A Summer 2016 Final Review 1 August 2016 Time Limit: 170 Minutes Name: 1. How many subsets are there for the set of cards in a standard playing card deck? How many subsets are there of size 8?
More informationImportant Distributions 7/17/2006
Important Distributions 7/17/2006 Discrete Uniform Distribution All outcomes of an experiment are equally likely. If X is a random variable which represents the outcome of an experiment of this type, then
More information