Midterm Examination Review Solutions MATH 210G Fall 2017

Size: px
Start display at page:

Download "Midterm Examination Review Solutions MATH 210G Fall 2017"

Transcription

1 Midterm Examination Review Solutions MATH 210G Fall 2017 Instructions: The midterm will be given in class on Thursday, March 16. You will be given the full class period. You will be expected to SHOW WORK to justify your solutions. NOTE: on the actual exam, there will be one true-false problem worth 5 points. There will be 6 additional problems each worth 20 points. You are to work five of them. So the total will be out of 105 points. You will be allowed a non-cellular calculator and an sheet with formulas on one side, which is to be turned in with the exam. 1. The first problem will be FIVE true/false items taken directly from quizzes or from quiz readings. The problem will be worth 5 points total. 2. Using the symbols K: I were the King of the world; C: I d throw away the cars in the world; B: I d throw away the bars in the world, transform each of the statements into logical symbols and use truth tables to determine which pairs of statements are logically equivalent. A) If I were the King of the world then I d throw way the cars and the bars in the world : K (C B) B) Either I were the King of the world or I d throw away the cars and the bars of the world: K (C B) C) Either I were not the King of the world or I d throw way the cars and the bars of the world K (C B) K C B C B K (C B) K (C B) K (C B) T T T T F T F T T F F T T T F T F F F T F F F F Looking at the fourth and fifth rows of the truth table we see that (A) and (C) are logically equivalent but (B) is not equivalent to (A) or (C).

2 K C B C B K (C B) K (C B) K (C B) T T T T T T T T F T F F T F F T T T T T T F F T F T F T T T F F F T F T F F F F T F F T F F T F T F F F F T F T 3. Translate each sentence into an implication of the form A B or B A, then determine the intended implication. Everyone who has bags of money also has thick biceps None but masons drink protein shakes No one with thick biceps can recite ancient poems People who like to go to the opera have bags of money All the masons can recite ancient poems Let s assign symbols: B: people with bags of money; T people who have thick biceps; M :masons; P: people who drink protein shakes; R: people who can recite ancient poems; O: people who like to go to the opera. These sentences translate into symbols as follows: B T P M R T B O M R. The implication chain is P M R T B 0, or P O. People who drink protein shakes don t like to go to the opera. 4. Translate each sentence into an implication of the form A B or B A, then determine the intended implication. Cowboys fans like to say I m fixin to leave People named Digby do not like to say I m fixin to leave People not named Digby are always named Bubba. People who like to use technology to their advantage are not named Bubba.

3 Fans of Super bowl Champs like to use technology to their advantage. Let s assign symbols as follows C: Cowboys fan; F : people who say I m fixin to leave; D: People names Digby; B: People named Bubba; I: People who like to use technology to their advantage; S: Fans of SuperBowl champs The sentences translate to: C F D F D B I B S I Then S I B D F C. Fans of Superbowl Champs are not Cowboys fans. 5. Suppose you run a medical clinic. Suppose that 10% of the patients who enter your clinic have a runny nose and suppose that 5% of the clinic s patients have a fever. Suppose it is known that 7% of person s with a runny nose are also have a fever. Use Bayes formula to compute the probability that a patient who enters your clinic and is running a fever also has a runny nose. Let A be the event that a patient has a runny nose and B be the event that a patient has a fever. Then p(a) = 0.1, p(b) = 0.05 and p(b A) = Bayes formula implies that p(a B) = p(b A)p(A)/p(B) = /0.05 = 0.14 or 14% probability that a patient who is a has a fever also has runny nose. 6. Using the identity p(x) = p(x A)p(A) + p(x A)p( A) one obtains from Bayes theorem that p(b A)p(A) p(a B) = p(b A)p(A) + p(b A)p( A) Note that p( A) = 1 p(a). Suppose that 1% of the population has a certain genetic defect D. A certain test detects the defect 90% of the time when the defect is present, but 9.6% of the tests are false positives. If a person tested for the defect has a positive test result, what is the probability that the person actually has the defect? Let D denote the event that a person has the genetic defect and let T denote the event that the test for the defect gives a positive result. We are given that p(t D) = 0.9 and that p(t D) = We also know that p(d) = 0.01 so p( D) = Applying the form of Bayes formula abive gives that p(d T ) = p(t D)p(D) p(t D)p(D) + p(t D)p( D) = = = or about 8.65% of those who get a positive test result actually have the defect. 7. In a multiple choice exam, 60% of students know the correct method to solve a certain problem. However, there is a 5% chance that a student will choose the wrong answer on the test, even if he/she knows the correct method to solve the problem, and there

4 is also a 25% chance that a student who does not know the correct method guesses the answer correctly. If a student did get the problem right, what is the probability that the student actually knew the correct answer? Let A be the event that a student knows the method to get the correct answer and let B be the event that the student actually gets the correct answer. Then p(a) = 0.6 and p(b A) = 0.95 since p( B A) = 0.05 and p(b A) = 0.25 while p( A) = 0.4. Note that p(b) = p(b A)p(A) + p(b A)p( A) = = 0.67 so Bayes rule gives p(a B) = p(b A)p(A) p(b) = Slightly over 85% of students who get the right answer know the method to get the right answer 8. Donald Trump and Vladimir Putin play a tournament as follows. They each wager 32 rubles. In each round they flip a fair coin. If it comes up heads Trump wins, tails Putin wins. The first player to win ten times gets the full 64 rubles. After fifteen rounds Melania Trump calls and tells Donald he has to come home for dinner. At this point Putin has won 9 times and Trump has won 6 times. What is the fairest way to divide the 64 rubles? The probability that Trump will win if play continues is one in sixteen, since Trump would need to get heads four consecutive times. So Trump should get 64/16 = 4 rubles and Putin should get 64 15/16 = 60 rubles. 9. Batman and Superman each wager $ 8 in a tournament of Rock, Paper, Scissors. The first to win 10 times takes all. After fifteen rounds not counting ties Batman has eight wins and Superman has seven. At this point, Batman has to retire to the batcave and get some sleep. What is the fairest way to divide the $16 that has been wagered? What is the minimum additional number of rounds (not counting ties) that guarantees a winner? There has to be a winner in at most four more games since either Batman will win at least two of them or Superman will win at least three of them. To determine the probabilities of each winning, make a table of all possible outcomes of the four games and count how many cases each wins, then divide by all possible outcomes. The sixteen possible outcomes are ( B means Batman wins and S means Superman wins): S BBBB BBBS BBSB BBSS BSBB BSBS BSSB BSSS SBBB SBBS SBSB SBSS SSBB SSBS SSSB SSSS Batman wins 11 of the 16 possible cases so Batman should get $ 11 and Superman should get $ 5.

5 10. (a) A ladder is 10 feet long. When the top of the ladder just touches the top a wall, the bottom of the ladder is 6 feet from the wall. How high is the wall? (b) TV screen size is measured diagonally across the screen. A widescreen TV has an aspect ratio of 16:9, meaning the ratio of its width to its height is 16/9. Suppose that a TV has a one inch boundary on each side of the screen. If Joe has a cabinet that is 34 inches wide, what is the largest screen size TV that he can fit in the cabinet? Problem cancelled 11. An octahedral die has eight sides, each with probability 1/8 of coming out on top. There are 64 possible outcomes of rolling a pair of octahedral dice, listed as follows. (1, 1) (1, 2) (1, 3) (1, 4) (1, 5) (1, 6) (1, 7) (1, 8) (2, 1) (2, 2) (2, 3) (2, 4) (2, 5) (2, 6) (2, 7) (2, 8) (3, 1) (3, 2) (3, 3) (3, 4) (3, 5) (3, 6) (3, 7) (3, 8) (4, 1) (4, 2) (4, 3) (4, 4) (4, 5) (4, 6) (4, 7) (4, 8) (5, 1) (5, 2) (5, 3) (5, 4) (5, 5) (5, 6) (5, 7) (5, 8) (6, 1) (6, 2) (6, 3) (6, 4) (6, 5) (6, 6) (6, 7) (6, 8) (7, 1) (7, 2) (7, 3) (7, 4) (7, 5) (7, 6) (7, 7) (7, 8) (8, 1) (8, 2) (8, 3) (8, 4) (8, 5) (8, 6) (8, 7) (8, 8) Compute the probability that the sum of the dice is 7 or 11. Compute the probability that the sum is 3, or 15. Compute the probability that both die show an odd number. Compute the probability that the sum of the dice is an even number. (a) There are six ways to get a sum of 7 ((1, 6), (2, 5),..., (6, 1)) and six ways to get a 11 ((3, 8),..., (8, 3)) so 12 ways to get a 7 or 11 so the probability is 12/64 = 3/16. (b) There are two ways to get a three ((1, 2), (2, 1)), and two to get a 15 ((7, 8), (8, 7), so the probability is 4/64 = 1/16. (c) There are 16 ways in which both die show an odd number so the probability is 16/64 = 1/4. (d) The sum of the dice is even if both dice are even or both dice are odd. There are 16 ways for even and 16 for odd, so the probability is 32/64 = 1/ a) In four-card guts, a hand consists of four cards dealt from a deck of 52 cards. Straights and flushes are not counted. How many possible four card guts hands are there? b) How many four card guts hands contain exactly two pairs? c) How many four card guts hands contain three of a kind but not four of a kind? d) How many four card guts hands do not contain a pair? (a) There are ( ) ! = 4 4! 48! = = = 270,725

6 To ( get two pairs you need two different ranks. The number of choices of two ranks is 13 ) 2 = 78. Since there are four suits and you are choosing two suits for each pair, there are ( ( 4 2) = 6 choices for the pair at the higher rank and 4 2) choices for the pair at the lower rank. The total number of distinct pairs then is = To get three of a kind note that there are thirteen ranks and four choices (one of the four suits cannot be represented). Then you have 48 choices for the remaining card at a different rank. So the total number of possible four card hands containing three of a kind is = To get the number of hands that have a pair but no better, first note that there three different ranks represented in the hand (the rank with the pair and the two other ranks). There are ( ) 13 3 ways to choose three different ranks. There are three possible choices for which rank has the pair (the upper rank, the middle rank, or the lower rank). There are ( 4 2) = 6 ways to get a pair in a given rank, and there are four different ) choices for each rank that does not have the pair. Altogether this gives us = 82,368 possible ways to get a pair but no better. ( 13 3 Note that to determine the number of hands that have no pairs, there are four different ranks, and four different choices for the card at each rank so ( ) = possible four card hands without a pair. Note that there are 13 ways to get four of a kind, 1 at each rank. These are all the possiblities. Adding up the number of ways to get all possibilities we get # 4 of a kind + # 3 of a kind + # two pairs + # one pair +# no pair = = 270, a) In five card poker, a hand consists of five cards dealt from a deck of 52 cards. How many possible five card poker hands are there? b) How many five card poker hands do not contain any pairs? c) How many five card poker hands do not contain any card higher than a ten (ie, A,K,Q,J)? (Hint: This is the same as counting the number of five card hands from a deck that only contains ranks 2 10.) d) How many five card poker hands contain exactly one card of each suit? (a) The number of five card poker hands is ( ) 52 = 52! = 5 5! 47! 120 = 2,598,960 (b) If a poker hand does not contain any pairs then it has five ranks and four ways to get the card in each rank. Multiplying these ways gives ( ) 13 # = = = = 1,317,888 5 (c) This is the same as the number of ways of choosing five cards from a deck with the ) A-J s removed, which has 36 cards, that is, = 376, 992 ( 36 5

7 (d) Zero 14. a) Starting with the first 4 rows of Pascal s triangle, compute the next five rows. The next rows are as follows: b) How many distinct subsets are there of a set having eight elements? In general, how many distinct subsets are there of a set having N elements? Hint: consider the cases N = 0, 1, 2, 3 and look for a pattern. The set containing no elements is called the empty set. The empty set is a subset of every set. In particular, the empty set has one subset and a set with one element has two distinct subsets: the empty set and the element itself. There are 2 8 = 256 different subsets. In general, a set with N elements has 2 N distinct subsets, including the empty set. This number is obtained by adding up all the numbers in the Nth row of Pascal s triangle since the numbers ( n k) give the number of k-element subsets of a set of n elements. c) Eight kids want to play a game of four on four basketball. How many distinct ways are there to divide the kids into two teams, each with four players? There are 35 ways: ( 8 4) = 70 but each time the group is split into two teams of four, the splitting counts two of the 70 ways of choosing four elements from a set of eight elements. 15. Let L stand for the statement: Rex Tillerson is Large and let C stand for the statement Rex Tillerson is in charge. Use truth tables to verify whether the following two statements are logically equivalent: (i) Rex Tillerson is neither Large nor in Charge : L C. (ii) Rex Tillerson is not Large or in Charge: (L C). (iii) Rex Tillerson is not Large and in Charge: (L C). Thus statements (i) and (ii) are logically equivalent but (iii) is not equivalent to (i) or (ii). 16. Fill in the values T or F for each of the rows and columns of the following truth table.

8 L C L C (L C) (L C) T T T F F T F F L C L C (L C) (L C) T T F F F T F F F T F T F F T F F T T T Table 1: Truth table for # 15 P Q P Q (P Q) P ((P Q) P ) Q T T T F F T F F Table 2: Filled in truth values P Q P Q (P Q) P ((P Q) P ) Q T T T T T T F F F T F T T F T F F T F T

9 Recall that this is the truth table for modus ponens, the way that affirms by affirming.

A Probability Work Sheet

A Probability Work Sheet A Probability Work Sheet October 19, 2006 Introduction: Rolling a Die Suppose Geoff is given a fair six-sided die, which he rolls. What are the chances he rolls a six? In order to solve this problem, we

More information

1. 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? 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 information

The 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. 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 information

Total. STAT/MATH 394 A - Autumn Quarter Midterm. Name: Student ID Number: Directions. Complete all questions.

Total. STAT/MATH 394 A - Autumn Quarter Midterm. Name: Student ID Number: Directions. Complete all questions. STAT/MATH 9 A - Autumn Quarter 015 - Midterm Name: Student ID Number: Problem 1 5 Total Points Directions. Complete all questions. You may use a scientific calculator during this examination; graphing

More information

The probability set-up

The probability set-up CHAPTER 2 The probability set-up 2.1. Introduction and basic theory We will have a sample space, denoted S (sometimes Ω) that consists of all possible outcomes. For example, if we roll two dice, the sample

More information

Contemporary 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 Time Limit: 90 Minutes No Scratch Paper Calculator Allowed: Scientific Contemporary Mathematics Math 1030 Sample Exam I Chapters 13-15 Time Limit: 90 Minutes No Scratch Paper Calculator Allowed: Scientific Name: The point value of each problem is in the left-hand margin.

More information

CSE 312: Foundations of Computing II Quiz Section #2: Inclusion-Exclusion, Pigeonhole, Introduction to Probability

CSE 312: Foundations of Computing II Quiz Section #2: Inclusion-Exclusion, Pigeonhole, Introduction to Probability CSE 312: Foundations of Computing II Quiz Section #2: Inclusion-Exclusion, Pigeonhole, Introduction to Probability Review: Main Theorems and Concepts Binomial Theorem: Principle of Inclusion-Exclusion

More information

MATH 215 DISCRETE MATHEMATICS INSTRUCTOR: P. WENG

MATH 215 DISCRETE MATHEMATICS INSTRUCTOR: P. WENG MATH DISCRETE MATHEMATICS INSTRUCTOR: P. WENG Counting and Probability Suggested Problems Basic Counting Skills, Inclusion-Exclusion, and Complement. (a An office building contains 7 floors and has 7 offices

More information

More Probability: Poker Hands and some issues in Counting

More Probability: Poker Hands and some issues in Counting More Probability: Poker Hands and some issues in Counting Data From Thursday Everybody flipped a pair of coins and recorded how many times they got two heads, two tails, or one of each. We saw that the

More information

CSE 312: Foundations of Computing II Quiz Section #2: Inclusion-Exclusion, Pigeonhole, Introduction to Probability (solutions)

CSE 312: Foundations of Computing II Quiz Section #2: Inclusion-Exclusion, Pigeonhole, Introduction to Probability (solutions) CSE 31: Foundations of Computing II Quiz Section #: Inclusion-Exclusion, Pigeonhole, Introduction to Probability (solutions) Review: Main Theorems and Concepts Binomial Theorem: x, y R, n N: (x + y) n

More information

Compound Probability. Set Theory. Basic Definitions

Compound Probability. Set Theory. Basic Definitions Compound Probability Set Theory A probability measure P is a function that maps subsets of the state space Ω to numbers in the interval [0, 1]. In order to study these functions, we need to know some basic

More information

Probability is often written as a simplified fraction, but it can also be written as a decimal or percent.

Probability is often written as a simplified fraction, but it can also be written as a decimal or percent. CHAPTER 1: PROBABILITY 1. Introduction to Probability L EARNING TARGET: I CAN DETERMINE THE PROBABILITY OF AN EVENT. What s the probability of flipping heads on a coin? Theoretically, it is 1/2 1 way to

More information

Week in Review #5 ( , 3.1)

Week in Review #5 ( , 3.1) Math 166 Week-in-Review - S. Nite 10/6/2012 Page 1 of 5 Week in Review #5 (2.3-2.4, 3.1) n( E) In general, the probability of an event is P ( E) =. n( S) Distinguishable Permutations Given a set of n objects

More information

Chapter 2. Permutations and Combinations

Chapter 2. Permutations and Combinations 2. Permutations and Combinations Chapter 2. Permutations and Combinations In this chapter, we define sets and count the objects in them. Example Let S be the set of students in this classroom today. Find

More information

Discrete Random Variables Day 1

Discrete 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 information

MTH 103 H Final Exam. 1. I study and I pass the course is an example of a. (a) conjunction (b) disjunction. (c) conditional (d) connective

MTH 103 H Final Exam. 1. I study and I pass the course is an example of a. (a) conjunction (b) disjunction. (c) conditional (d) connective MTH 103 H Final Exam Name: 1. I study and I pass the course is an example of a (a) conjunction (b) disjunction (c) conditional (d) connective 2. Which of the following is equivalent to (p q)? (a) p q (b)

More information

November 11, Chapter 8: Probability: The Mathematics of Chance

November 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 information

Chapter 1. Probability

Chapter 1. Probability Chapter 1. Probability 1.1 Basic Concepts Scientific method a. For a given problem, we define measures that explains the problem well. b. Data is collected with observation and the measures are calculated.

More information

Counting Methods and Probability

Counting Methods and Probability CHAPTER Counting Methods and Probability Many good basketball players can make 90% of their free throws. However, the likelihood of a player making several free throws in a row will be less than 90%. You

More information

University of Connecticut Department of Mathematics

University of Connecticut Department of Mathematics University of Connecticut Department of Mathematics Math 070Q Exam A Fall 07 Name: TA Name: Discussion: Read This First! This is a closed notes, closed book exam. You cannot receive aid on this exam from

More information

The probability set-up

The probability set-up CHAPTER The probability set-up.1. Introduction and basic theory We will have a sample space, denoted S sometimes Ω that consists of all possible outcomes. For example, if we roll two dice, the sample space

More information

LC OL Probability. ARNMaths.weebly.com. As part of Leaving Certificate Ordinary Level Math you should be able to complete the following.

LC OL Probability. ARNMaths.weebly.com. As part of Leaving Certificate Ordinary Level Math you should be able to complete the following. A Ryan LC OL Probability ARNMaths.weebly.com Learning Outcomes As part of Leaving Certificate Ordinary Level Math you should be able to complete the following. Counting List outcomes of an experiment Apply

More information

Section Introduction to Sets

Section Introduction to Sets Section 1.1 - Introduction to Sets Definition: A set is a well-defined collection of objects usually denoted by uppercase letters. Definition: The elements, or members, of a set are denoted by lowercase

More information

Probability (Devore Chapter Two)

Probability (Devore Chapter Two) Probability (Devore Chapter Two) 1016-351-01 Probability Winter 2011-2012 Contents 1 Axiomatic Probability 2 1.1 Outcomes and Events............................... 2 1.2 Rules of Probability................................

More information

The 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. 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 information

STAT 311 (Spring 2016) Worksheet: W3W: Independence due: Mon. 2/1

STAT 311 (Spring 2016) Worksheet: W3W: Independence due: Mon. 2/1 Name: Group 1. For all groups. It is important that you understand the difference between independence and disjoint events. For each of the following situations, provide and example that is not in the

More information

Probability and Counting Techniques

Probability 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 information

Name: Class: Date: 6. An event occurs, on average, every 6 out of 17 times during a simulation. The experimental probability of this event is 11

Name: Class: Date: 6. An event occurs, on average, every 6 out of 17 times during a simulation. The experimental probability of this event is 11 Class: Date: Sample Mastery # Multiple Choice Identify the choice that best completes the statement or answers the question.. One repetition of an experiment is known as a(n) random variable expected value

More information

Roll & Make. Represent It a Different Way. Show Your Number as a Number Bond. Show Your Number on a Number Line. Show Your Number as a Strip Diagram

Roll & Make. Represent It a Different Way. Show Your Number as a Number Bond. Show Your Number on a Number Line. Show Your Number as a Strip Diagram Roll & Make My In Picture Form In Word Form In Expanded Form With Money Represent It a Different Way Make a Comparison Statement with a Greater than Your Make a Comparison Statement with a Less than Your

More information

Contents 2.1 Basic Concepts of Probability Methods of Assigning Probabilities Principle of Counting - Permutation and Combination 39

Contents 2.1 Basic Concepts of Probability Methods of Assigning Probabilities Principle of Counting - Permutation and Combination 39 CHAPTER 2 PROBABILITY Contents 2.1 Basic Concepts of Probability 38 2.2 Probability of an Event 39 2.3 Methods of Assigning Probabilities 39 2.4 Principle of Counting - Permutation and Combination 39 2.5

More information

Class XII Chapter 13 Probability Maths. Exercise 13.1

Class 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 information

Mathacle. Name: Date:

Mathacle. Name: Date: Quiz Probability 1.) A telemarketer knows from past experience that when she makes a call, the probability that someone will answer the phone is 0.20. What is probability that the next two phone calls

More information

Week 1: Probability models and counting

Week 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 information

Section 6.1 #16. Question: What is the probability that a five-card poker hand contains a flush, that is, five cards of the same suit?

Section 6.1 #16. Question: What is the probability that a five-card poker hand contains a flush, that is, five cards of the same suit? Section 6.1 #16 What is the probability that a five-card 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 information

Section The Multiplication Principle and Permutations

Section 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 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. More 9.-9.3 Practice Name MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question. Answer the question. ) In how many ways can you answer the questions on

More information

The point value of each problem is in the left-hand margin. You must show your work to receive any credit, except on problems 1 & 2. Work neatly.

The point value of each problem is in the left-hand 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 5-7 4 Problem Pages 4 Formula/Table Pages Time Limit: 90 Minutes 1 No Scratch Paper Calculator Allowed: Scientific Name: The point value of

More information

CHAPTER 2 PROBABILITY. 2.1 Sample Space. 2.2 Events

CHAPTER 2 PROBABILITY. 2.1 Sample Space. 2.2 Events CHAPTER 2 PROBABILITY 2.1 Sample Space A probability model consists of the sample space and the way to assign probabilities. Sample space & sample point The sample space S, is the set of all possible outcomes

More information

Math 1001: Excursions in Mathematics Final Exam: 9 May :30-4:30 p.m.

Math 1001: Excursions in Mathematics Final Exam: 9 May :30-4:30 p.m. Math 1001: Excursions in Mathematics Final Exam: 9 May 2011 1:30-4:30 p.m. Name: Section Number: You have three hours to complete this exam. There are ten problems on twelve pages, worth a total of 100

More information

Honors Precalculus Chapter 9 Summary Basic Combinatorics

Honors Precalculus Chapter 9 Summary Basic Combinatorics Honors Precalculus Chapter 9 Summary Basic Combinatorics A. Factorial: n! means 0! = Why? B. Counting principle: 1. How many different ways can a license plate be formed a) if 7 letters are used and each

More information

8.2 Union, Intersection, and Complement of Events; Odds

8.2 Union, Intersection, and Complement of Events; Odds 8.2 Union, Intersection, and Complement of Events; Odds Since we defined an event as a subset of a sample space it is natural to consider set operations like union, intersection or complement in the context

More information

Junior 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, 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 information

Math 102 Practice for Test 3

Math 102 Practice for Test 3 Math 102 Practice for Test 3 Name Show your work and write all fractions and ratios in simplest form for full credit. 1. If you draw a single card from a standard 52-card deck what is P(King face card)?

More information

Discrete Structures Lecture Permutations and Combinations

Discrete Structures Lecture Permutations and Combinations Introduction Good morning. Many counting problems can be solved by finding the number of ways to arrange a specified number of distinct elements of a set of a particular size, where the order of these

More information

Discrete Structures for Computer Science

Discrete 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 information

BALTIMORE COUNTY PUBLIC SCHOOLS. Rock n Roll

BALTIMORE COUNTY PUBLIC SCHOOLS. Rock n Roll Number cube labeled 1-6 (A template to make a cube is at the back of this packet.)36 counters Rock n Roll Paper Pencil None The first player rolls the number cube to find out how many groups of counters

More information

Counting and Probability Math 2320

Counting and Probability Math 2320 Counting and Probability Math 2320 For a finite set A, the number of elements of A is denoted by A. We have two important rules for counting. 1. Union rule: Let A and B be two finite sets. Then A B = A

More information

Chapter 1. Probability

Chapter 1. Probability Chapter 1. Probability 1.1 Basic Concepts Scientific method a. For a given problem, we define measures that explains the problem well. b. Data is collected with observation and the measures are calculated.

More information

Problem Set 2. Counting

Problem Set 2. Counting Problem Set 2. Counting 1. (Blitzstein: 1, Q3 Fred is planning to go out to dinner each night of a certain week, Monday through Friday, with each dinner being at one of his favorite ten restaurants. i

More information

Option 1: You could simply list all the possibilities: wool + red wool + green wool + black. cotton + green cotton + black

Option 1: You could simply list all the possibilities: wool + red wool + green wool + black. cotton + green cotton + black ACTIVITY 6.2 CHOICES 713 OBJECTIVES ACTIVITY 6.2 Choices 1. Apply the multiplication principle of counting. 2. Determine the sample space for a probability distribution. 3. Display a sample space with

More information

Advanced Intermediate Algebra Chapter 12 Summary INTRO TO PROBABILITY

Advanced Intermediate Algebra Chapter 12 Summary INTRO TO PROBABILITY Advanced Intermediate Algebra Chapter 12 Summary INTRO TO PROBABILITY 1. Jack and Jill do not like washing dishes. They decide to use a random method to select whose turn it is. They put some red and blue

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. Study Guide for Test III (MATH 1630) Name MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question. Find the number of subsets of the set. 1) {x x is an even

More information

Week 3 Classical Probability, Part I

Week 3 Classical Probability, Part I Week 3 Classical Probability, Part I Week 3 Objectives Proper understanding of common statistical practices such as confidence intervals and hypothesis testing requires some familiarity with probability

More information

Section : Combinations and Permutations

Section : Combinations and Permutations Section 11.1-11.2: 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 information

Elementary Statistics. Basic Probability & Odds

Elementary 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 information

3 The multiplication rule/miscellaneous counting problems

3 The multiplication rule/miscellaneous counting problems Practice for Exam 1 1 Axioms of probability, disjoint and independent events 1 Suppose P (A 0, P (B 05 (a If A and B are independent, what is P (A B? What is P (A B? (b If A and B are disjoint, what is

More information

Raise your hand if you rode a bus within the past month. Record the number of raised hands.

Raise 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 information

Math 4610, Problems to be Worked in Class

Math 4610, Problems to be Worked in Class Math 4610, Problems to be Worked in Class Bring this handout to class always! You will need it. If you wish to use an expanded version of this handout with space to write solutions, you can download one

More information

CS1802 Week 9: Probability, Expectation, Entropy

CS1802 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 information

Independent and Mutually Exclusive Events

Independent and Mutually Exclusive Events Independent and Mutually Exclusive Events By: OpenStaxCollege Independent and mutually exclusive do not mean the same thing. Independent Events Two events are independent if the following are true: P(A

More information

n(s)=the number of ways an event can occur, assuming all ways are equally likely to occur. p(e) = n(e) n(s)

n(s)=the number of ways an event can occur, assuming all ways are equally likely to occur. p(e) = n(e) n(s) The following story, taken from the book by Polya, Patterns of Plausible Inference, Vol. II, Princeton Univ. Press, 1954, p.101, is also quoted in the book by Szekely, Classical paradoxes of probability

More information

6.041/6.431 Spring 2009 Quiz 1 Wednesday, March 11, 7:30-9:30 PM.

6.041/6.431 Spring 2009 Quiz 1 Wednesday, March 11, 7:30-9:30 PM. 6.04/6.43 Spring 09 Quiz Wednesday, March, 7:30-9:30 PM. Name: Recitation Instructor: TA: Question Part Score Out of 0 3 all 40 2 a 5 b 5 c 6 d 6 3 a 5 b 6 c 6 d 6 e 6 f 6 g 0 6.04 Total 00 6.43 Total

More information

Math1116Chapter15ProbabilityProbabilityDone.notebook January 20, 2013

Math1116Chapter15ProbabilityProbabilityDone.notebook January 20, 2013 Chapter 15 Notes on Probability 15.4 Probability Spaces Probability assignment A function that assigns to each event E a number between 0 and 1, which represents the probability of the event E and which

More information

Finite Math Section 6_4 Solutions and Hints

Finite Math Section 6_4 Solutions and Hints Finite Math Section 6_4 Solutions and Hints by Brent M. Dingle for the book: Finite Mathematics, 7 th Edition by S. T. Tan. DO NOT PRINT THIS OUT AND TURN IT IN!!!!!!!! This is designed to assist you in

More information

TEST A CHAPTER 11, PROBABILITY

TEST 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 information

MAT 17: Introduction to Mathematics Final Exam Review Packet. B. Use the following definitions to write the indicated set for each exercise below:

MAT 17: Introduction to Mathematics Final Exam Review Packet. B. Use the following definitions to write the indicated set for each exercise below: MAT 17: Introduction to Mathematics Final Exam Review Packet A. Using set notation, rewrite each set definition below as the specific collection of elements described enclosed in braces. Use the following

More information

Math Exam 2 Review. NOTE: For reviews of the other sections on Exam 2, refer to the first page of WIR #4 and #5.

Math Exam 2 Review. NOTE: For reviews of the other sections on Exam 2, refer to the first page of WIR #4 and #5. Math 166 Fall 2008 c Heather Ramsey Page 1 Math 166 - Exam 2 Review NOTE: For reviews of the other sections on Exam 2, refer to the first page of WIR #4 and #5. Section 3.2 - Measures of Central Tendency

More information

Math Exam 2 Review. NOTE: For reviews of the other sections on Exam 2, refer to the first page of WIR #4 and #5.

Math Exam 2 Review. NOTE: For reviews of the other sections on Exam 2, refer to the first page of WIR #4 and #5. Math 166 Fall 2008 c Heather Ramsey Page 1 Math 166 - Exam 2 Review NOTE: For reviews of the other sections on Exam 2, refer to the first page of WIR #4 and #5. Section 3.2 - Measures of Central Tendency

More information

2 A fair coin is flipped 8 times. What is the probability of getting more heads than tails? A. 1 2 B E. NOTA

2 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 information

Empirical (or statistical) probability) is based on. The empirical probability of an event E is the frequency of event E.

Empirical (or statistical) probability) is based on. The empirical probability of an event E is the frequency of event E. Probability and Statistics Chapter 3 Notes Section 3-1 I. Probability Experiments. A. When weather forecasters say There is a 90% chance of rain tomorrow, or a doctor says There is a 35% chance of a successful

More information

Lenarz Math 102 Practice Exam # 3 Name: 1. A 10-sided die is rolled 100 times with the following results:

Lenarz Math 102 Practice Exam # 3 Name: 1. A 10-sided die is rolled 100 times with the following results: Lenarz Math 102 Practice Exam # 3 Name: 1. A 10-sided die is rolled 100 times with the following results: Outcome Frequency 1 8 2 8 3 12 4 7 5 15 8 7 8 8 13 9 9 10 12 (a) What is the experimental probability

More information

Such a description is the basis for a probability model. Here is the basic vocabulary we use.

Such a description is the basis for a probability model. Here is the basic vocabulary we use. 5.2.1 Probability Models When we toss a coin, we can t know the outcome in advance. What do we know? We are willing to say that the outcome will be either heads or tails. We believe that each of these

More information

Dependence. Math Circle. October 15, 2016

Dependence. Math Circle. October 15, 2016 Dependence Math Circle October 15, 2016 1 Warm up games 1. Flip a coin and take it if the side of coin facing the table is a head. Otherwise, you will need to pay one. Will you play the game? Why? 2. If

More information

November 6, Chapter 8: Probability: The Mathematics of Chance

November 6, Chapter 8: Probability: The Mathematics of Chance Chapter 8: Probability: The Mathematics of Chance November 6, 2013 Last Time Crystallographic notation Groups Crystallographic notation The first symbol is always a p, which indicates that the pattern

More information

Chapter 5 - Elementary Probability Theory

Chapter 5 - Elementary Probability Theory Chapter 5 - Elementary Probability Theory Historical Background Much of the early work in probability concerned games and gambling. One of the first to apply probability to matters other than gambling

More information

Math : Probabilities

Math : Probabilities 20 20. Probability EP-Program - Strisuksa School - Roi-et Math : Probabilities Dr.Wattana Toutip - Department of Mathematics Khon Kaen University 200 :Wattana Toutip wattou@kku.ac.th http://home.kku.ac.th/wattou

More information

Name: Exam Score: /100. Exam 1: Version C. Academic Honesty Pledge

Name: Exam Score: /100. Exam 1: Version C. Academic Honesty Pledge MATH 11008 Explorations in Modern Mathematics Fall 2013 Circle one: MW7:45 / MWF1:10 Dr. Kracht Name: Exam Score: /100. (110 pts available) Exam 1: Version C Academic Honesty Pledge Your signature at the

More information

6) A) both; happy B) neither; not happy C) one; happy D) one; not happy

6) A) both; happy B) neither; not happy C) one; happy D) one; not happy MATH 00 -- PRACTICE TEST 2 Millersville University, Spring 202 Ron Umble, Instr. MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question. Find all natural

More information

1.5 How Often Do Head and Tail Occur Equally Often?

1.5 How Often Do Head and Tail Occur Equally Often? 4 Problems.3 Mean Waiting Time for vs. 2 Peter and Paula play a simple game of dice, as follows. Peter keeps throwing the (unbiased) die until he obtains the sequence in two successive throws. For Paula,

More information

1. 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 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 information

Intermediate Math Circles November 1, 2017 Probability I

Intermediate 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 information

5.6. Independent Events. INVESTIGATE the Math. Reflecting

5.6. Independent Events. INVESTIGATE the Math. Reflecting 5.6 Independent Events YOU WILL NEED calculator EXPLORE The Fortin family has two children. Cam determines the probability that the family has two girls. Rushanna determines the probability that the family

More information

Exam III Review Problems

Exam 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 Week-in-Reviews

More information

Math 14 Lecture Notes Ch. 3.3

Math 14 Lecture Notes Ch. 3.3 3.3 Two Basic Rules of Probability If we want to know the probability of drawing a 2 on the first card and a 3 on the 2 nd card from a standard 52-card deck, the diagram would be very large and tedious

More information

Statistics 1040 Summer 2009 Exam III

Statistics 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 information

CHAPTER 7 Probability

CHAPTER 7 Probability CHAPTER 7 Probability 7.1. Sets A set is a well-defined collection of distinct objects. Welldefined means that we can determine whether an object is an element of a set or not. Distinct means that we can

More information

MATH CALCULUS & STATISTICS/BUSN - PRACTICE EXAM #1 - SPRING DR. DAVID BRIDGE

MATH CALCULUS & STATISTICS/BUSN - PRACTICE EXAM #1 - SPRING DR. DAVID BRIDGE MATH 205 - CALCULUS & STATISTICS/BUSN - PRACTICE EXAM # - SPRING 2006 - DR. DAVID BRIDGE TRUE/FALSE. Write 'T' if the statement is true and 'F' if the statement is false. Tell whether the statement is

More information

Probability Warm-Up 2

Probability Warm-Up 2 Probability Warm-Up 2 Directions Solve to the best of your ability. (1) Write out the sample space (all possible outcomes) for the following situation: A dice is rolled and then a color is chosen, blue

More information

PROBABILITY TOPIC TEST MU ALPHA THETA 2007

PROBABILITY TOPIC TEST MU ALPHA THETA 2007 PROBABILITY TOPI TEST MU ALPHA THETA 00. Richard has red marbles and white marbles. Richard s friends, Vann and Penelo, each select marbles from the bag. What is the probability that Vann selects red marble

More information

MAT104: 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 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 information

Probability MAT230. Fall Discrete Mathematics. MAT230 (Discrete Math) Probability Fall / 37

Probability 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 information

Probability 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, 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 information

Probability. The MEnTe Program Math Enrichment through Technology. Title V East Los Angeles College

Probability. The MEnTe Program Math Enrichment through Technology. Title V East Los Angeles College Probability The MEnTe Program Math Enrichment through Technology Title V East Los Angeles College 2003 East Los Angeles College. All rights reserved. Topics Introduction Empirical Probability Theoretical

More information

STAT 430/510 Probability Lecture 3: Space and Event; Sample Spaces with Equally Likely Outcomes

STAT 430/510 Probability Lecture 3: Space and Event; Sample Spaces with Equally Likely Outcomes STAT 430/510 Probability Lecture 3: Space and Event; Sample Spaces with Equally Likely Outcomes Pengyuan (Penelope) Wang May 25, 2011 Review We have discussed counting techniques in Chapter 1. (Principle

More information

Math116Chapter15ProbabilityProbabilityDone.notebook January 08, 2012

Math116Chapter15ProbabilityProbabilityDone.notebook January 08, 2012 15.4 Probability Spaces Probability assignment A function that assigns to each event E a number between 0 and 1, which represents the probability of the event E and which we denote by Pr (E). Probability

More information

MATH CALCULUS & STATISTICS/BUSN - PRACTICE EXAM #1 - SPRING DR. DAVID BRIDGE

MATH CALCULUS & STATISTICS/BUSN - PRACTICE EXAM #1 - SPRING DR. DAVID BRIDGE MATH 2053 - CALCULUS & STATISTICS/BUSN - PRACTICE EXAM #1 - SPRING 2009 - DR. DAVID BRIDGE MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question. Solve the

More information

LISTING THE WAYS. getting a total of 7 spots? possible ways for 2 dice to fall: then you win. But if you roll. 1 q 1 w 1 e 1 r 1 t 1 y

LISTING THE WAYS. getting a total of 7 spots? possible ways for 2 dice to fall: then you win. But if you roll. 1 q 1 w 1 e 1 r 1 t 1 y LISTING THE WAYS A pair of dice are to be thrown getting a total of 7 spots? There are What is the chance of possible ways for 2 dice to fall: 1 q 1 w 1 e 1 r 1 t 1 y 2 q 2 w 2 e 2 r 2 t 2 y 3 q 3 w 3

More information

Name: Final Exam May 7, 2014

Name: 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 information

November 8, Chapter 8: Probability: The Mathematics of Chance

November 8, Chapter 8: Probability: The Mathematics of Chance Chapter 8: Probability: The Mathematics of Chance November 8, 2013 Last Time Probability Models and Rules Discrete Probability Models Equally Likely Outcomes Crystallographic notation The first symbol

More information

CIS 2033 Lecture 6, Spring 2017

CIS 2033 Lecture 6, Spring 2017 CIS 2033 Lecture 6, Spring 2017 Instructor: David Dobor February 2, 2017 In this lecture, we introduce the basic principle of counting, use it to count subsets, permutations, combinations, and partitions,

More information