Jan 31 Homework Solutions Math 151, Winter Chapter 3 Problems (pages )

Size: px
Start display at page:

Download "Jan 31 Homework Solutions Math 151, Winter 2012. Chapter 3 Problems (pages 102-110)"

Transcription

1 Jan 31 Homework Solutions Math 151, Winter 01 Chapter 3 Problems (pages ) Problem 61 Genes relating to albinism are denoted by A and a. Only those people who receive the a gene from both parents will be albino. Persons having the gene pair A, a are normal in appearance and, because they can pass on the trait to their offspring, are called carriers. Suppose that a normal couple has two children, exactly one of whom is an albino. Suppose that the nonalbino child mates with a person who is known to be a carrier for albinism. (a) What is the probability that their first offspring is an albino? For the first offspring to be an albino, both parents would have to be carriers. We have P (offspring is aa) P (offspring is aa both parents are Aa)P (both parents are Aa). If both parents are Aa, then the offspring is albino with probability 1/4. Hence P (offspring is aa both parents are Aa) 1 4. Now let s compute P (both parents are Aa). One parent of the offspring is known to be a carrier. We know that the other parent is normal. We also know that the other parent must be the offspring of two carriers, because the other parent has two normal parents and an albino sibling. Hence P (both parents are Aa) P (other parent is Aa) since one parent is known to be a carrier P (other parent is Aa other parent is normal) 3. since other parent is known to be normal P (other parent is Aa and normal) by definition P (other parent is normal) P (other parent is Aa) since any Aa person is normal P (other parent is normal) P (other parent is Aa) P (other parent is AA) + P (other parent is Aa) 1/ 1/4 + 1/ 1

2 Thus P (offspring is aa) P (offspring is aa both parents are Aa)P (both parents are Aa) (b) What is the conditional probability that their second offspring is an albino given that their first born is not? We know P (nd is albino 1st is normal) We calculate the denominator P (1st is normal and nd is albino) P (1st is normal) using part (a). P (1st is normal) 1 P (1st is albino) If the first offspring is normal and the second offspring is albino, then their parents must be carriers, so P (1st offspring is normal and nd is albino) P (1st offspring is normal and nd is albino both parents are Aa)P (both parents are Aa). If the parents are both carriers, the first offspring is normal with probability 3/4 and the second is albino with probability 1/4. By Part (a), both parents are carriers with probability /3. Thus P (1st offspring is normal and nd is albino) P (1st offspring is normal and nd is albino both parents are Aa)P (both parents are Aa) 4 1 ) In conclusion, we have P (nd is albino 1st is normal) P (1st is normal and nd is albino) P (1st is normal) 1/8 5/ Problem 64 A true-false question is to be posed to a husband-and-wife team on a quiz show. Both the husband and the wife will independently give the correct answer with probability p. Which of the following is a better strategy for the couple? (a) Choose one of them and let that person answer the question.

3 (b) Have them both consider the question, and then either given the common answer if they agree or, if they disagree, flip a coin to determine which answer to give. Under strategy (a), we have P (correct answer) P (correct answer wife is chosen)p (wife is chosen) Under strategy (b), we have +P (correct answer husband is chosen)p (husband is chosen) p 1 + p 1 p. P (correct answer) P (correct answer both are correct)p (both are correct) +P (correct answer only wife is correct)p (only wife is correct) +P (correct answer only husband is correct)p (only husband is correct) +P (correct answer both are wrong)p (both are wrong) 1 p + 1 p(1 p) + 1 p(1 p) + 0 (1 p) p, using the fact that if only one of the wife or husband is correct, then there is a 1/ probability the coin will land so that the correct answer is given. Therefore, the two strategies work equally well. Problem 69 A certain organism possesses a pair of each of 5 different genes (which we will designate by the first 5 letters of the alphabet). Each gene appears in forms (which we will designate by lowercase and capital letters). The capital letter will be assumed to be the dominant gene, in the sense that if an organism possesses the gene pair xx, then it will outwardly have the appearance of the X gene. For instance, if X stands for brown eyes and x for blue eyes, then an individual having either gene pair XX or xx will have brown eyes, whereas one having gene pair xx will have blue eyes. The characteristic appearance of an organism is called its phenotype, whereas its genetic constitution is called its genotype. (Thus, organisms with respective genotypes aa, bb, cc, dd, ee and AA, BB, cc, DD, ee would have different genotypes but the same phenotype.) In a mating between organisms, each one contributes, at random, one of its gene pairs of each type. The 5 contributions of an organism (one of each of the 5 types) are assumed to be independent and are also independent of the contributions of the organism s mate. In a mating between organisms having genotypes aa, bb, cc, dd, ee and aa, bb, cc, Dd, ee what is the probability that the progeny will (i) phenotypically and (ii) genotypically resemble (a) the first parent? For the A gene, the possible genotypes are aa and aa, both occurring with probability 1/. Thus for the A gene, the progeny will have the same phenotype as the first parent with probability 1/. For the B gene, the possible genotypes are bb, bb, and BB with respective probabilities 1/4, 1/, 1/4. Thus for the B gene, the progeny will have the same phenotype as the first parent with probability 3/4. Do 3

4 this for all 5 genes. The probability that the progeny and first parent will have the same phenotype is P (matches 1st parent s phenotype) P (A correct)p (B correct)p (C correct)p (D correct)p (E correct) For the A gene, the progeny will have the same genotype as the first parent with probability 1/. For the B gene, the progeny will have the same genotype as the first parent with probability 1/. Do this for all 5 genes. The probability that the progeny and first parent will have the same genotype is P (matches 1st parent s genotype) P (A correct)p (B correct)p (C correct)p (D correct)p (E correct) (b) the second parent? P (matches nd parent s phenotype) P (A correct)p (B correct)p (C correct)p (D correct)p (E correct) P (matches nd parent s genotype) P (A correct)p (B correct)p (C correct)p (D correct)p (E correct) (c) either parent? 4

5 P (matches either parent s phenotype) P (matches 1st parent s phenotype) + P (matches nd parent s phenotype) since the two events are disjoint P (matches either parent s genotype) P (matches 1st parent s genotype) + P (matches nd parent s genotype) since the two events are disjoint (d) neither parent? P (matches neither parent s phenotype) 1 P (matches either parent s phenotype) P (matches neither parent s genotype) 1 P (matches either parent s genotype) Problem 76 Suppose that E and F are mutually exclusive events of an experiment. Show that if independent trials of this experiment are performed, then E will occur before F with probability P (E)/[P (E) + P (F )]. Define the event G as the event that neither E nor F occurs. That is, G E c F c. P (E occurs before F ) P (E occurs before F trial 1 is E)P (trial 1 is E) +P (E occurs before F trial 1 is F )P (trial 1 is F ) +P (E occurs before F trial 1 is G)P (trial 1 is G). 5

6 If E occurs on trial 1, then E occurs before F, and if F occurs on trial 1, then E does not occur before F. If G occurs on trial 1, then we start all over in determining whether E or F occurs first. Thus P (E occurs before F ) 1 P (E) + 0 P (F ) + P (E occurs before F )P (G). Solving for P (E occurs before F) yields P (E occurs before F ) P (E) 1 P (G) P (E) P (E) + P (F ). Problem 78 A and B play a series of games. Each game is independently won by A with probability p and by B with probability 1 p. They stop when the total number of wins of one of the players is two greater than that of the other player. The player with the greater number of total wins is declared the winner of the series. (a) Find the probability that a total of 4 games are played. If A wins both of the first two games, the games end before 4 games are played. Similarly if B wins the first two games. The probability that A and B are tied after two games is p(1 p). If A and B are tied after two games, then the only way the game will stop after 4 games is if either A wins the next two games, which occurs with probability p, or B wins the next two games, which occurs with probability (1 p). In other words, if A and B are tied after two games, the probability that there will be exactly 4 games played is p + (1 p). So P (exactly 4 games played) P (exactly 4 games played tied after two games)p (tied after two games) ) (p + (1 p) p(1 p) 4p 4 + 8p 3 6p + p. (b) Find the probability that A is the winner of the series. P (A wins) P (A wins A wins after two games)p (A wins after two games) +P (A wins B wins after two games)p (B wins after two games) +P (A wins tie after two games)p (tie after two games) 1 p + 0 (1 p) + P (A wins) p(1 p). Solving for P (A wins), we get P (A wins) p 1 p + p. 6

7 Problem 80 In a certain contest, the players are of equal skill and the probability is 1/ that a specified one of the two contestants will be the victor. In a group of n players, the players are paired off against each other at random. The n 1 winners are again paired off randomly, and so on, until a single winner remains. Consider two specified contestants, A and B, and define the events A i, i n, by A plays in exactly i contests, and E by A and B never play each other. (a) Find P (A i ), i 1,...n. In order for A to play in exactly i contests, player A will have to win the first i 1 contests and lose the i-th contest. Hence ( 1 ) i 1 1 P (A i ) 1. i (b) Find P (E). First observe if A and B play, then one must beat the other, so We have P (E) 1 P (E c ) 1 P (A ever beats B) P (B ever beats A) 1 P (B ever beats A) by symmetry. P (B ever beats A) n P (B ever beats A A i )P (A i ). i1 If A loses the i-th contest, he loses to any one of the n 1 other players with equal probability, so P (B ever beats A A i ) 1 n 1. Therefore Hence P (B ever beats A) n P (B ever beats A A i )P (A i ) i1 n i1 1 n 1 1 n 1 1 by part (a) i n i1 1 i 1 n (1/)n 1/ 1 n. P (E) 1 P (B ever beats A) ( 1 ) 1 n 1 1 n 1. 7 since it s a geometric series

8 (c) Let P n P (E). Show that P n 4 + P ) n 1 n 4 n 1 and use this formula to check the answer you obtained in part (b). Note: there is a mistake in the recursive formula given in the book. The formula they give is for E c in place of E. We instead prove the correct recursive formula for E. We define P i to be the event that A and B do not play each other in a tournament with i players. Hence P n P (E). Let F be the event that A and B play in the first contest and observe that P n P (E) P (E F )P (F ) + P (E F c )P (F c ). Since A plays each of the n 1 other players in the first contest with equal probability, P (F ) 1 and P (F c ) n. Note P (E F ) 0. To calculate P (E F c ), n 1 n 1 note that if A and B do not play in the first contest, then there are two mutually exclusive ways that they will not play in the tournament. The first way is that one of A and B loses in the first round, which happens with probability 3. The second 4 way is that both both A and B win in the first round and A and B don t meet in the subsequent tournament with n 1 players. This happens with probability 1 P 4 n 1 P n 1. Hence 4 and P n P (E) P (E F c ) P n 1 4 P (E F )P (F ) + P (E F c )P (F c ) 1 0 n P ) n 1 n 4 n P ) n 1 n 4 n 1. Now we can check part (b), in which we found that P (E) 1 1 n 1, using induction on n. The base case is n 1. Clearly if there are only 1 players, then A and B must play in the first round and so our formula is correct. P n For the inductive step, suppose that formula P n holds for n 1. We n must show that the formula P n 1 1 holds for n. Using our formula above, n 1 8

9 we have P n 4 + P ) n 1 n 4 n ) n ) n n n 1 ( n 1 ) n n n 1 n n 1 1 n 1. n n 1 Hence by induction on n, we have proven the formula P (E) P n 1 1 n 1 from part (b) for all positive values of n. (d) Explain why n 1 games are played. Number these games, and let B i denote the event that A and B play each other in game i, i 1,..., n 1. In each game, exactly one player loses. Since there is a single winner remaining after the tournament, all but one of the n players lose a game. Thus the number of games is n 1. (e) What is P (B i )? Two of the n players play in game i and each pair of players play in game i with equal probability, so (f) Use part (e) to find P (E). P (B i ) ( 1 n)!(n )! n! Note E ( n 1 i1 B i) c. Hence ( ) P (E) 1 P n 1 i1 B i 1 n 1 i1 P (B i ) n n 1 ( n 1) i1 1 ( n 1) 1 1 n 1. n ( n 1) 1 n 1 ( n 1). since the events B i are mutually exclusive 1 n 1 ( n 1) Note this is the same answer we found in part (b). 9

10 Problem 81 An investor owns shares in a stock whose present value is 5. She has decided that she must sell her stock if it either goes down to 10 or up to 40. If each change of price is either up 1 point with probability.55 or down 1 point with probability.45, and the successive changes are independent, what is the probability that the investor retires a winner? Let P n be the probability that the investor retires a winner given that she owns stock whose present value is n, 10 n 40. Note P 10 0 and P By Bayes formula, P n P (winner price goes up to n + 1)P (price goes up) +P (winner price goes down to n 1)P (price goes down) P n P n Let s try to solve for the difference P n+1 P n. From the equation we get that Rearranging, we get Hence P n P n P n (P n P n 1 ).55(P n+1 P n ). P n+1 P n (.45/.55)(P n P n 1 ). P n+1 P n (.45/.55)(P n P n 1 ) (.45/.55) n 10 (P 11 P 10 ) (.45/.55) n 10 P 11 since P To compute P 11, note that 1 P 40 P n10 (P n+1 P n ) 39 n10 (.45/.55) n 10 P 11 1 (.45/.55) /.55 P 11, where the last equality comes from the sum of a geometric series. So Thus P 5 is given by P 5 P 5 P 10 P /.55 1 (.45/.55) n10 4 (P n+1 P n ) (.45/.55) n 10 P 11 n10 1 (.45/.55) /.55 P 11 1 (.45/.55) /.55 1 (.45/.55)15 1 (.45/.55) /.55 1 (.45/.55) 30 10

11 Chapter 3 Theoretical Exercises (pages ) Problem 1 The Ballot Problem. In an election, candidate A receives n votes and candidate B receives m votes, where n > m. Assuming that all of the (n + m)!/n!m! orderings of the votes are equally likely, let P n,m denote the probability that A is always ahead in the counting of the votes. (a) Compute P,1, P 3,1, P 3,, P 4,1, P 4,, P 4,3. For n, m 1, the possible orderings are AAB, ABA, BAA, so P,1 1/3. For n 3, m 1, the possible orderings are AAAB, AABA, ABAA, BAAA, so P 3,1 1/. For n 3, m, of the 10 possible orderings, A stays ahead for AABAB and AAABB, so P 3, 1/5. For n 4, m 1, the possible orderings are AAAAB, AAABA, AABAA, ABAAA, and BAAAA, so P 4,1 3/5. For n 4, m, of the 15 possible orderings, A stays ahead for AABABA, AABAAB, AAABBA, AAABAB, AAAABB, so P 4, 1/3. For n 4, m 3, of the 35 possible orderings, A stays ahead for AABABAB, AABAABB, AAABBAB, AAABABB, and AAAABBB, so P 4,3 1/7. (b) Find P n,1, P n,. If m 1, there are n + 1 possible orderings. A must win the first two votes to say ahead and B can win one of any of the last n 1 votes. Thus P n,1 n 1. If m, n+1 there are ( ) n+ possible orderings. The first four votes must be AAAA, AAAB, or AABA, so there are ( ) ( n + n ) ( 1 + n ) ( 1 n ) + (n ) orderings where A stays ahead. Thus ( n ) + (n ) P n, ( n+ ) (n )(n 3)/ + (n ) (n + )(n + 1)/ (n )(n + 1)/ (n + )(n + 1)/ n n + (c) On the basis of your results in parts (a) and (b), conjecture the value of P n,m. We conjecture that P n,m n m n+m for all values of n and m with n > m. (d) Derive a recursion for P n,m in terms of P n 1,m and P n,m 1 by conditioning on who receives the last vote. By Bayes formula P (A stays ahead) P (A stays ahead last vote is A)P (last vote is A) +P (A stays ahead last vote is B)P (last vote is B). 11

12 Regardless of who gets the last vote, A stays ahead until and including the last vote. The probability that the last vote is for A is n/(n + m) and the probability that the last vote is for B is m/(n + m), so P n,m P n 1,m n n + m + P m n,m 1 n + m. (e) Use part (d) to verify your conjecture in part (c) by an induction proof on n + m. The base case n + m 3 is verified in part (a). For the inductive step, suppose P n,m n m if n + m N for some integer N. This is our inductive assumption. n+m Now, consider n + m N + 1. We have m n + m n n + m + n m + 1 n P n,m P n 1,m n + m + P n,m 1 n 1 m n 1 + m n + m 1 by inductive assumption (n 1 m)n + (n m + 1)m (n + m 1)(n + m) n n m + m (n + m 1)(n + m) (n + m 1)(n m) (n + m 1)(n + m) n m n + m. m n + m Hence by induction on n + m, we have proven that P n,m n m holds for all values n+m of n and m with n > m. Chapter 4 Problems (pages ) Problem 1 Two balls are chosen randomly from an urn containing 8 white, 4 black, and orange balls. Suppose that we win $ for each black ball selected and we lose $1 for each white ball selected. Let X denote our winnings. What are the possible values of X, and what are the probabilities associated with each value? There are at most six possible values for X depending what balls are chosen. If two white balls are chosen, X. If a white and orange ball is chosen, X 1. If two orange balls are chosen, X 0. If a white and black ball is chosen, X 1. If a black and orange ball is chosen, X. If two black balls are chosen, X 4. Thus X takes six values, 1, 0, 1,, 4. Let s calculate the probabilities associated with each value. ( 8 ) P {X } ( 14 ).3077 P {X 1} 8 ( 14 )

13 ( ) P {X 0} ( 14 ).0110 P {X 1} 8 4 ( 14 ).3516 P {X } 4 ( 14 ).0879 P {X 4} ( 4 ) ( 14 ).0659 Problem 4 Five men and five women are ranked according to their scores on an examination. Assume that no two scores are alike and all 10! possible rankings are equally likely. Let X denote the highest ranking acheived by a woman (For instance, X 1 if the top-ranked person is female.) Find P {X i}, i 1,, 3,..., 8, 9, 10. First note there is at least one woman of rank at least 6, so P {X i} 0 for i 7, 8, 9, 10. Let i 6 and suppose the highest rank of a woman is i. Then there are i 1 men of higher rank than her, who can be chosen and ordered in ( 5 i 1) (i 1)! different ways. There are 5 choices of women for the i-th rank. There are 10 i people of lower rank, who can be ordered in (10 i)! ways. Thus for i 1,,..., 6. P {X i} ( 5 i 1) (i 1)! 5 (10 i)! 10! Problem 5 Let X represent the difference between the number of heads and the number of tails obtained when a coin is tossed n times. What are the possible values of X? If a coin is tossed n times, the number of tails is some integer i between 0 and n and the number of heads is n i. So X takes the values (n i) i n i for i 0, 1,..., n. 13

Definition and Calculus of Probability

Definition and Calculus of Probability In experiments with multivariate outcome variable, knowledge of the value of one variable may help predict another. For now, the word prediction will mean update the probabilities of events regarding the

More information

Feb 7 Homework Solutions Math 151, Winter 2012. Chapter 4 Problems (pages 172-179)

Feb 7 Homework Solutions Math 151, Winter 2012. Chapter 4 Problems (pages 172-179) Feb 7 Homework Solutions Math 151, Winter 2012 Chapter Problems (pages 172-179) Problem 3 Three dice are rolled. By assuming that each of the 6 3 216 possible outcomes is equally likely, find the probabilities

More information

Fundamentele Informatica II

Fundamentele Informatica II Fundamentele Informatica II Answer to selected exercises 1 John C Martin: Introduction to Languages and the Theory of Computation M.M. Bonsangue (and J. Kleijn) Fall 2011 Let L be a language. It is clear

More information

Homework 3 (due Tuesday, October 13)

Homework 3 (due Tuesday, October 13) Homework (due Tuesday, October 1 Problem 1. Consider an experiment that consists of determining the type of job either blue-collar or white-collar and the political affiliation Republican, Democratic,

More information

Statistics 100A Homework 3 Solutions

Statistics 100A Homework 3 Solutions Chapter Statistics 00A Homework Solutions Ryan Rosario. Two balls are chosen randomly from an urn containing 8 white, black, and orange balls. Suppose that we win $ for each black ball selected and we

More information

WORKED EXAMPLES 1 TOTAL PROBABILITY AND BAYES THEOREM

WORKED EXAMPLES 1 TOTAL PROBABILITY AND BAYES THEOREM WORKED EXAMPLES 1 TOTAL PROBABILITY AND BAYES THEOREM EXAMPLE 1. A biased coin (with probability of obtaining a Head equal to p > 0) is tossed repeatedly and independently until the first head is observed.

More information

Homework 3 Solution, due July 16

Homework 3 Solution, due July 16 Homework 3 Solution, due July 16 Problems from old actuarial exams are marked by a star. Problem 1*. Upon arrival at a hospital emergency room, patients are categorized according to their condition as

More information

LAB : PAPER PET GENETICS. male (hat) female (hair bow) Skin color green or orange Eyes round or square Nose triangle or oval Teeth pointed or square

LAB : PAPER PET GENETICS. male (hat) female (hair bow) Skin color green or orange Eyes round or square Nose triangle or oval Teeth pointed or square Period Date LAB : PAPER PET GENETICS 1. Given the list of characteristics below, you will create an imaginary pet and then breed it to review the concepts of genetics. Your pet will have the following

More information

2 GENETIC DATA ANALYSIS

2 GENETIC DATA ANALYSIS 2.1 Strategies for learning genetics 2 GENETIC DATA ANALYSIS We will begin this lecture by discussing some strategies for learning genetics. Genetics is different from most other biology courses you have

More information

Probabilistic Strategies: Solutions

Probabilistic Strategies: Solutions Probability Victor Xu Probabilistic Strategies: Solutions Western PA ARML Practice April 3, 2016 1 Problems 1. You roll two 6-sided dice. What s the probability of rolling at least one 6? There is a 1

More information

6.3 Conditional Probability and Independence

6.3 Conditional Probability and Independence 222 CHAPTER 6. PROBABILITY 6.3 Conditional Probability and Independence Conditional Probability Two cubical dice each have a triangle painted on one side, a circle painted on two sides and a square painted

More information

WHERE DOES THE 10% CONDITION COME FROM?

WHERE DOES THE 10% CONDITION COME FROM? 1 WHERE DOES THE 10% CONDITION COME FROM? The text has mentioned The 10% Condition (at least) twice so far: p. 407 Bernoulli trials must be independent. If that assumption is violated, it is still okay

More information

Chapter 4 Lecture Notes

Chapter 4 Lecture Notes Chapter 4 Lecture Notes Random Variables October 27, 2015 1 Section 4.1 Random Variables A random variable is typically a real-valued function defined on the sample space of some experiment. For instance,

More information

Math 3C Homework 3 Solutions

Math 3C Homework 3 Solutions Math 3C Homework 3 s Ilhwan Jo and Akemi Kashiwada ilhwanjo@math.ucla.edu, akashiwada@ucla.edu Assignment: Section 2.3 Problems 2, 7, 8, 9,, 3, 5, 8, 2, 22, 29, 3, 32 2. You draw three cards from a standard

More information

2. How many ways can the letters in PHOENIX be rearranged? 7! = 5,040 ways.

2. How many ways can the letters in PHOENIX be rearranged? 7! = 5,040 ways. Math 142 September 27, 2011 1. How many ways can 9 people be arranged in order? 9! = 362,880 ways 2. How many ways can the letters in PHOENIX be rearranged? 7! = 5,040 ways. 3. The letters in MATH are

More information

AP: LAB 8: THE CHI-SQUARE TEST. Probability, Random Chance, and Genetics

AP: LAB 8: THE CHI-SQUARE TEST. Probability, Random Chance, and Genetics Ms. Foglia Date AP: LAB 8: THE CHI-SQUARE TEST Probability, Random Chance, and Genetics Why do we study random chance and probability at the beginning of a unit on genetics? Genetics is the study of inheritance,

More information

Discrete Math in Computer Science Homework 7 Solutions (Max Points: 80)

Discrete Math in Computer Science Homework 7 Solutions (Max Points: 80) Discrete Math in Computer Science Homework 7 Solutions (Max Points: 80) CS 30, Winter 2016 by Prasad Jayanti 1. (10 points) Here is the famous Monty Hall Puzzle. Suppose you are on a game show, and you

More information

ECON 459 Game Theory. Lecture Notes Auctions. Luca Anderlini Spring 2015

ECON 459 Game Theory. Lecture Notes Auctions. Luca Anderlini Spring 2015 ECON 459 Game Theory Lecture Notes Auctions Luca Anderlini Spring 2015 These notes have been used before. If you can still spot any errors or have any suggestions for improvement, please let me know. 1

More information

Basic Probability Concepts

Basic Probability Concepts page 1 Chapter 1 Basic Probability Concepts 1.1 Sample and Event Spaces 1.1.1 Sample Space A probabilistic (or statistical) experiment has the following characteristics: (a) the set of all possible outcomes

More information

Question of the Day. Key Concepts. Vocabulary. Mathematical Ideas. QuestionofDay

Question of the Day. Key Concepts. Vocabulary. Mathematical Ideas. QuestionofDay QuestionofDay Question of the Day What is the probability that in a family with two children, both are boys? What is the probability that in a family with two children, both are boys, if we already know

More information

Statistics 100A Homework 2 Solutions

Statistics 100A Homework 2 Solutions Statistics Homework Solutions Ryan Rosario Chapter 9. retail establishment accepts either the merican Express or the VIS credit card. total of percent of its customers carry an merican Express card, 6

More information

REPEATED TRIALS. The probability of winning those k chosen times and losing the other times is then p k q n k.

REPEATED TRIALS. The probability of winning those k chosen times and losing the other times is then p k q n k. REPEATED TRIALS Suppose you toss a fair coin one time. Let E be the event that the coin lands heads. We know from basic counting that p(e) = 1 since n(e) = 1 and 2 n(s) = 2. Now suppose we play a game

More information

Solutions for Practice problems on proofs

Solutions for Practice problems on proofs Solutions for Practice problems on proofs Definition: (even) An integer n Z is even if and only if n = 2m for some number m Z. Definition: (odd) An integer n Z is odd if and only if n = 2m + 1 for some

More information

Math 202-0 Quizzes Winter 2009

Math 202-0 Quizzes Winter 2009 Quiz : Basic Probability Ten Scrabble tiles are placed in a bag Four of the tiles have the letter printed on them, and there are two tiles each with the letters B, C and D on them (a) Suppose one tile

More information

Variations on a Human Face Lab

Variations on a Human Face Lab Variations on a Human Face Lab Introduction: Have you ever wondered why everybody has a different appearance even if they are closely related? It is because of the large variety or characteristics that

More information

36 Odds, Expected Value, and Conditional Probability

36 Odds, Expected Value, and Conditional Probability 36 Odds, Expected Value, and Conditional Probability What s the difference between probabilities and odds? To answer this question, let s consider a game that involves rolling a die. If one gets the face

More information

Math 55: Discrete Mathematics

Math 55: Discrete Mathematics Math 55: Discrete Mathematics UC Berkeley, Fall 2011 Homework # 5, due Wednesday, February 22 5.1.4 Let P (n) be the statement that 1 3 + 2 3 + + n 3 = (n(n + 1)/2) 2 for the positive integer n. a) What

More information

Math 408, Actuarial Statistics I, Spring 2008. Solutions to combinatorial problems

Math 408, Actuarial Statistics I, Spring 2008. Solutions to combinatorial problems , Spring 2008 Word counting problems 1. Find the number of possible character passwords under the following restrictions: Note there are 26 letters in the alphabet. a All characters must be lower case

More information

Statistics 100A Homework 4 Solutions

Statistics 100A Homework 4 Solutions Chapter 4 Statistics 00A Homework 4 Solutions Ryan Rosario 39. A ball is drawn from an urn containing 3 white and 3 black balls. After the ball is drawn, it is then replaced and another ball is drawn.

More information

Department of Industrial Engineering IE 202: Engineering Statistics Example Questions Spring 2012

Department of Industrial Engineering IE 202: Engineering Statistics Example Questions Spring 2012 Department of Industrial Engineering IE 202: Engineering Statistics Example Questions Spring 202. Twenty workers are to be assigned to 20 different jobs, one to each job. How many different assignments

More information

Chapter 6. 1. What is the probability that a card chosen from an ordinary deck of 52 cards is an ace? Ans: 4/52.

Chapter 6. 1. What is the probability that a card chosen from an ordinary deck of 52 cards is an ace? Ans: 4/52. Chapter 6 1. What is the probability that a card chosen from an ordinary deck of 52 cards is an ace? 4/52. 2. What is the probability that a randomly selected integer chosen from the first 100 positive

More information

AP Stats - Probability Review

AP Stats - Probability Review AP Stats - Probability Review Multiple Choice Identify the choice that best completes the statement or answers the question. 1. I toss a penny and observe whether it lands heads up or tails up. Suppose

More information

Discrete Mathematics and Probability Theory Fall 2009 Satish Rao, David Tse Note 10

Discrete Mathematics and Probability Theory Fall 2009 Satish Rao, David Tse Note 10 CS 70 Discrete Mathematics and Probability Theory Fall 2009 Satish Rao, David Tse Note 10 Introduction to Discrete Probability Probability theory has its origins in gambling analyzing card games, dice,

More information

LAB : THE CHI-SQUARE TEST. Probability, Random Chance, and Genetics

LAB : THE CHI-SQUARE TEST. Probability, Random Chance, and Genetics Period Date LAB : THE CHI-SQUARE TEST Probability, Random Chance, and Genetics Why do we study random chance and probability at the beginning of a unit on genetics? Genetics is the study of inheritance,

More information

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

Question: What is the probability that a five-card poker hand contains a flush, that is, five cards of the same suit? ECS20 Discrete Mathematics Quarter: Spring 2007 Instructor: John Steinberger Assistant: Sophie Engle (prepared by Sophie Engle) Homework 8 Hints Due Wednesday June 6 th 2007 Section 6.1 #16 What is the

More information

Math 319 Problem Set #3 Solution 21 February 2002

Math 319 Problem Set #3 Solution 21 February 2002 Math 319 Problem Set #3 Solution 21 February 2002 1. ( 2.1, problem 15) Find integers a 1, a 2, a 3, a 4, a 5 such that every integer x satisfies at least one of the congruences x a 1 (mod 2), x a 2 (mod

More information

Bayesian Tutorial (Sheet Updated 20 March)

Bayesian Tutorial (Sheet Updated 20 March) Bayesian Tutorial (Sheet Updated 20 March) Practice Questions (for discussing in Class) Week starting 21 March 2016 1. What is the probability that the total of two dice will be greater than 8, given that

More information

Bayesian Nash Equilibrium

Bayesian Nash Equilibrium . Bayesian Nash Equilibrium . In the final two weeks: Goals Understand what a game of incomplete information (Bayesian game) is Understand how to model static Bayesian games Be able to apply Bayes Nash

More information

Genetics for the Novice

Genetics for the Novice Genetics for the Novice by Carol Barbee Wait! Don't leave yet. I know that for many breeders any article with the word genetics in the title causes an immediate negative reaction. Either they quickly turn

More information

Lecture Note 1 Set and Probability Theory. MIT 14.30 Spring 2006 Herman Bennett

Lecture Note 1 Set and Probability Theory. MIT 14.30 Spring 2006 Herman Bennett Lecture Note 1 Set and Probability Theory MIT 14.30 Spring 2006 Herman Bennett 1 Set Theory 1.1 Definitions and Theorems 1. Experiment: any action or process whose outcome is subject to uncertainty. 2.

More information

Sample Induction Proofs

Sample Induction Proofs Math 3 Worksheet: Induction Proofs III, Sample Proofs A.J. Hildebrand Sample Induction Proofs Below are model solutions to some of the practice problems on the induction worksheets. The solutions given

More information

AN ANALYSIS OF A WAR-LIKE CARD GAME. Introduction

AN ANALYSIS OF A WAR-LIKE CARD GAME. Introduction AN ANALYSIS OF A WAR-LIKE CARD GAME BORIS ALEXEEV AND JACOB TSIMERMAN Abstract. In his book Mathematical Mind-Benders, Peter Winkler poses the following open problem, originally due to the first author:

More information

3.2 Roulette and Markov Chains

3.2 Roulette and Markov Chains 238 CHAPTER 3. DISCRETE DYNAMICAL SYSTEMS WITH MANY VARIABLES 3.2 Roulette and Markov Chains In this section we will be discussing an application of systems of recursion equations called Markov Chains.

More information

Lecture 13. Understanding Probability and Long-Term Expectations

Lecture 13. Understanding Probability and Long-Term Expectations Lecture 13 Understanding Probability and Long-Term Expectations Thinking Challenge What s the probability of getting a head on the toss of a single fair coin? Use a scale from 0 (no way) to 1 (sure thing).

More information

Probability and Expected Value

Probability and Expected Value Probability and Expected Value This handout provides an introduction to probability and expected value. Some of you may already be familiar with some of these topics. Probability and expected value are

More information

Minimax Strategies. Minimax Strategies. Zero Sum Games. Why Zero Sum Games? An Example. An Example

Minimax Strategies. Minimax Strategies. Zero Sum Games. Why Zero Sum Games? An Example. An Example Everyone who has studied a game like poker knows the importance of mixing strategies With a bad hand, you often fold But you must bluff sometimes Lectures in Microeconomics-Charles W Upton Zero Sum Games

More information

ECE-316 Tutorial for the week of June 1-5

ECE-316 Tutorial for the week of June 1-5 ECE-316 Tutorial for the week of June 1-5 Problem 35 Page 176: refer to lecture notes part 2, slides 8, 15 A box contains 5 red and 5 blue marbles. Two marbles are withdrawn randomly. If they are the same

More information

Section 6-5 Sample Spaces and Probability

Section 6-5 Sample Spaces and Probability 492 6 SEQUENCES, SERIES, AND PROBABILITY 52. How many committees of 4 people are possible from a group of 9 people if (A) There are no restrictions? (B) Both Juan and Mary must be on the committee? (C)

More information

That s Not Fair! ASSESSMENT #HSMA20. Benchmark Grades: 9-12

That s Not Fair! ASSESSMENT #HSMA20. Benchmark Grades: 9-12 That s Not Fair! ASSESSMENT # Benchmark Grades: 9-12 Summary: Students consider the difference between fair and unfair games, using probability to analyze games. The probability will be used to find ways

More information

Mathematical goals. Starting points. Materials required. Time needed

Mathematical goals. Starting points. Materials required. Time needed Level S2 of challenge: B/C S2 Mathematical goals Starting points Materials required Time needed Evaluating probability statements To help learners to: discuss and clarify some common misconceptions about

More information

Week 2: Conditional Probability and Bayes formula

Week 2: Conditional Probability and Bayes formula Week 2: Conditional Probability and Bayes formula We ask the following question: suppose we know that a certain event B has occurred. How does this impact the probability of some other A. This question

More information

A Few Basics of Probability

A Few Basics of Probability A Few Basics of Probability Philosophy 57 Spring, 2004 1 Introduction This handout distinguishes between inductive and deductive logic, and then introduces probability, a concept essential to the study

More information

DNA Determines Your Appearance!

DNA Determines Your Appearance! DNA Determines Your Appearance! Summary DNA contains all the information needed to build your body. Did you know that your DNA determines things such as your eye color, hair color, height, and even the

More information

Current California Math Standards Balanced Equations

Current California Math Standards Balanced Equations Balanced Equations Current California Math Standards Balanced Equations Grade Three Number Sense 1.0 Students understand the place value of whole numbers: 1.1 Count, read, and write whole numbers to 10,000.

More information

Estimating Probability Distributions

Estimating Probability Distributions Estimating Probability Distributions Readings: Manning and Schutze, Section 6.2 Jurafsky & Martin, Section 6.3 One of the central problems we face in using probability models for NLP is obtaining the actual

More information

Chapter 5. Discrete Probability Distributions

Chapter 5. Discrete Probability Distributions Chapter 5. Discrete Probability Distributions Chapter Problem: Did Mendel s result from plant hybridization experiments contradicts his theory? 1. Mendel s theory says that when there are two inheritable

More information

Number Theory. Proof. Suppose otherwise. Then there would be a finite number n of primes, which we may

Number Theory. Proof. Suppose otherwise. Then there would be a finite number n of primes, which we may Number Theory Divisibility and Primes Definition. If a and b are integers and there is some integer c such that a = b c, then we say that b divides a or is a factor or divisor of a and write b a. Definition

More information

Genetics 1. Defective enzyme that does not make melanin. Very pale skin and hair color (albino)

Genetics 1. Defective enzyme that does not make melanin. Very pale skin and hair color (albino) Genetics 1 We all know that children tend to resemble their parents. Parents and their children tend to have similar appearance because children inherit genes from their parents and these genes influence

More information

Ch. 13.2: Mathematical Expectation

Ch. 13.2: Mathematical Expectation Ch. 13.2: Mathematical Expectation Random Variables Very often, we are interested in sample spaces in which the outcomes are distinct real numbers. For example, in the experiment of rolling two dice, we

More information

1 Gambler s Ruin Problem

1 Gambler s Ruin Problem Coyright c 2009 by Karl Sigman 1 Gambler s Ruin Problem Let N 2 be an integer and let 1 i N 1. Consider a gambler who starts with an initial fortune of $i and then on each successive gamble either wins

More information

Ch5: Discrete Probability Distributions Section 5-1: Probability Distribution

Ch5: Discrete Probability Distributions Section 5-1: Probability Distribution Recall: Ch5: Discrete Probability Distributions Section 5-1: Probability Distribution A variable is a characteristic or attribute that can assume different values. o Various letters of the alphabet (e.g.

More information

Contemporary Mathematics- MAT 130. Probability. a) What is the probability of obtaining a number less than 4?

Contemporary Mathematics- MAT 130. Probability. a) What is the probability of obtaining a number less than 4? Contemporary Mathematics- MAT 30 Solve the following problems:. A fair die is tossed. What is the probability of obtaining a number less than 4? What is the probability of obtaining a number less than

More information

Math 115 Spring 2011 Written Homework 5 Solutions

Math 115 Spring 2011 Written Homework 5 Solutions . Evaluate each series. a) 4 7 0... 55 Math 5 Spring 0 Written Homework 5 Solutions Solution: We note that the associated sequence, 4, 7, 0,..., 55 appears to be an arithmetic sequence. If the sequence

More information

Fundamentals of Probability

Fundamentals of Probability Fundamentals of Probability Introduction Probability is the likelihood that an event will occur under a set of given conditions. The probability of an event occurring has a value between 0 and 1. An impossible

More information

ST 371 (IV): Discrete Random Variables

ST 371 (IV): Discrete Random Variables ST 371 (IV): Discrete Random Variables 1 Random Variables A random variable (rv) is a function that is defined on the sample space of the experiment and that assigns a numerical variable to each possible

More information

DOUBLES TENNIS LEAGUE *The following rules provided by Purdue Intramural Sports are not meant to be all encompassing.*

DOUBLES TENNIS LEAGUE *The following rules provided by Purdue Intramural Sports are not meant to be all encompassing.* DOUBLES TENNIS LEAGUE *The following rules provided by Purdue Intramural Sports are not meant to be all encompassing.* SECTION 1. TOURNAMENT FORMAT I. League Overview A. The league will consist of a five

More information

DOUBLES TENNIS LEAGUE

DOUBLES TENNIS LEAGUE DOUBLES TENNIS LEAGUE *The following rules provided by Purdue Intramural Sports are not meant to be all encompassing. Please refer to the Participant Manual for comprehensive eligibility guidelines, policies,

More information

Additional Probability Problems

Additional Probability Problems Additional Probability Problems 1. A survey has shown that 52% of the women in a certain community work outside the home. Of these women, 64% are married, while 86% of the women who do not work outside

More information

Chapter 16. Law of averages. Chance. Example 1: rolling two dice Sum of draws. Setting up a. Example 2: American roulette. Summary.

Chapter 16. Law of averages. Chance. Example 1: rolling two dice Sum of draws. Setting up a. Example 2: American roulette. Summary. Overview Box Part V Variability The Averages Box We will look at various chance : Tossing coins, rolling, playing Sampling voters We will use something called s to analyze these. Box s help to translate

More information

I Have...Who Has... Multiplication Game

I Have...Who Has... Multiplication Game How to play the game: Distribute the cards randomly to your students. Some students may get more than one card. Select a student to begin by reading their card aloud. (example: 35. who has 4x4?) 35 4 x

More information

Section 1.3 P 1 = 1 2. = 1 4 2 8. P n = 1 P 3 = Continuing in this fashion, it should seem reasonable that, for any n = 1, 2, 3,..., = 1 2 4.

Section 1.3 P 1 = 1 2. = 1 4 2 8. P n = 1 P 3 = Continuing in this fashion, it should seem reasonable that, for any n = 1, 2, 3,..., = 1 2 4. Difference Equations to Differential Equations Section. The Sum of a Sequence This section considers the problem of adding together the terms of a sequence. Of course, this is a problem only if more than

More information

E3: PROBABILITY AND STATISTICS lecture notes

E3: PROBABILITY AND STATISTICS lecture notes E3: PROBABILITY AND STATISTICS lecture notes 2 Contents 1 PROBABILITY THEORY 7 1.1 Experiments and random events............................ 7 1.2 Certain event. Impossible event............................

More information

PERMUTATIONS AND COMBINATIONS HOW TO AVOID THEM AT ALL COSTS AND STILL ACTUALLY UNDERSTAND AND DO COUNTING PROBLEMS WITH EASE!

PERMUTATIONS AND COMBINATIONS HOW TO AVOID THEM AT ALL COSTS AND STILL ACTUALLY UNDERSTAND AND DO COUNTING PROBLEMS WITH EASE! PERMUTATIONS AND COMBINATIONS HOW TO AVOID THEM AT ALL COSTS AND STILL ACTUALLY UNDERSTAND AND DO COUNTING PROBLEMS WITH EASE! A BRIEF FOUR-STEP PROGRAM James Tanton www.jamestanton.com COMMENT: If I were

More information

Lecture 1 Introduction Properties of Probability Methods of Enumeration Asrat Temesgen Stockholm University

Lecture 1 Introduction Properties of Probability Methods of Enumeration Asrat Temesgen Stockholm University Lecture 1 Introduction Properties of Probability Methods of Enumeration Asrat Temesgen Stockholm University 1 Chapter 1 Probability 1.1 Basic Concepts In the study of statistics, we consider experiments

More information

Colored Hats and Logic Puzzles

Colored Hats and Logic Puzzles Colored Hats and Logic Puzzles Alex Zorn January 21, 2013 1 Introduction In this talk we ll discuss a collection of logic puzzles/games in which a number of people are given colored hats, and they try

More information

Heredity. Sarah crosses a homozygous white flower and a homozygous purple flower. The cross results in all purple flowers.

Heredity. Sarah crosses a homozygous white flower and a homozygous purple flower. The cross results in all purple flowers. Heredity 1. Sarah is doing an experiment on pea plants. She is studying the color of the pea plants. Sarah has noticed that many pea plants have purple flowers and many have white flowers. Sarah crosses

More information

Binomial lattice model for stock prices

Binomial lattice model for stock prices Copyright c 2007 by Karl Sigman Binomial lattice model for stock prices Here we model the price of a stock in discrete time by a Markov chain of the recursive form S n+ S n Y n+, n 0, where the {Y i }

More information

Thursday, October 18, 2001 Page: 1 STAT 305. Solutions

Thursday, October 18, 2001 Page: 1 STAT 305. Solutions Thursday, October 18, 2001 Page: 1 1. Page 226 numbers 2 3. STAT 305 Solutions S has eight states Notice that the first two letters in state n +1 must match the last two letters in state n because they

More information

Problems 1-6: In tomato fruit, red flesh color is dominant over yellow flesh color, Use R for the Red allele and r for the yellow allele.

Problems 1-6: In tomato fruit, red flesh color is dominant over yellow flesh color, Use R for the Red allele and r for the yellow allele. Genetics Problems Name ANSWER KEY Problems 1-6: In tomato fruit, red flesh color is dominant over yellow flesh color, Use R for the Red allele and r for the yellow allele. 1. What would be the genotype

More information

SECTION 10-5 Multiplication Principle, Permutations, and Combinations

SECTION 10-5 Multiplication Principle, Permutations, and Combinations 10-5 Multiplication Principle, Permutations, and Combinations 761 54. Can you guess what the next two rows in Pascal s triangle, shown at right, are? Compare the numbers in the triangle with the binomial

More information

4. Continuous Random Variables, the Pareto and Normal Distributions

4. Continuous Random Variables, the Pareto and Normal Distributions 4. Continuous Random Variables, the Pareto and Normal Distributions A continuous random variable X can take any value in a given range (e.g. height, weight, age). The distribution of a continuous random

More information

arxiv:1112.0829v1 [math.pr] 5 Dec 2011

arxiv:1112.0829v1 [math.pr] 5 Dec 2011 How Not to Win a Million Dollars: A Counterexample to a Conjecture of L. Breiman Thomas P. Hayes arxiv:1112.0829v1 [math.pr] 5 Dec 2011 Abstract Consider a gambling game in which we are allowed to repeatedly

More information

Regular Languages and Finite State Machines

Regular Languages and Finite State Machines Regular Languages and Finite State Machines Plan for the Day: Mathematical preliminaries - some review One application formal definition of finite automata Examples 1 Sets A set is an unordered collection

More information

Exam 3 Review/WIR 9 These problems will be started in class on April 7 and continued on April 8 at the WIR.

Exam 3 Review/WIR 9 These problems will be started in class on April 7 and continued on April 8 at the WIR. Exam 3 Review/WIR 9 These problems will be started in class on April 7 and continued on April 8 at the WIR. 1. Urn A contains 6 white marbles and 4 red marbles. Urn B contains 3 red marbles and two white

More information

Section 5-3 Binomial Probability Distributions

Section 5-3 Binomial Probability Distributions Section 5-3 Binomial Probability Distributions Key Concept This section presents a basic definition of a binomial distribution along with notation, and methods for finding probability values. Binomial

More information

C H A P T E R Regular Expressions regular expression

C H A P T E R Regular Expressions regular expression 7 CHAPTER Regular Expressions Most programmers and other power-users of computer systems have used tools that match text patterns. You may have used a Web search engine with a pattern like travel cancun

More information

Introduction to Hypothesis Testing

Introduction to Hypothesis Testing I. Terms, Concepts. Introduction to Hypothesis Testing A. In general, we do not know the true value of population parameters - they must be estimated. However, we do have hypotheses about what the true

More information

Tiers, Preference Similarity, and the Limits on Stable Partners

Tiers, Preference Similarity, and the Limits on Stable Partners Tiers, Preference Similarity, and the Limits on Stable Partners KANDORI, Michihiro, KOJIMA, Fuhito, and YASUDA, Yosuke February 7, 2010 Preliminary and incomplete. Do not circulate. Abstract We consider

More information

Genetics with a Smile

Genetics with a Smile Teacher Notes Materials Needed: Two coins (penny, poker chip, etc.) per student - One marked F for female and one marked M for male Copies of student worksheets - Genetics with a Smile, Smiley Face Traits,

More information

DETERMINE whether the conditions for a binomial setting are met. COMPUTE and INTERPRET probabilities involving binomial random variables

DETERMINE whether the conditions for a binomial setting are met. COMPUTE and INTERPRET probabilities involving binomial random variables 1 Section 7.B Learning Objectives After this section, you should be able to DETERMINE whether the conditions for a binomial setting are met COMPUTE and INTERPRET probabilities involving binomial random

More information

Elements of probability theory

Elements of probability theory 2 Elements of probability theory Probability theory provides mathematical models for random phenomena, that is, phenomena which under repeated observations yield di erent outcomes that cannot be predicted

More information

Section 7C: The Law of Large Numbers

Section 7C: The Law of Large Numbers Section 7C: The Law of Large Numbers Example. You flip a coin 00 times. Suppose the coin is fair. How many times would you expect to get heads? tails? One would expect a fair coin to come up heads half

More information

SCORE SETS IN ORIENTED GRAPHS

SCORE SETS IN ORIENTED GRAPHS Applicable Analysis and Discrete Mathematics, 2 (2008), 107 113. Available electronically at http://pefmath.etf.bg.ac.yu SCORE SETS IN ORIENTED GRAPHS S. Pirzada, T. A. Naikoo The score of a vertex v in

More information

a 11 x 1 + a 12 x 2 + + a 1n x n = b 1 a 21 x 1 + a 22 x 2 + + a 2n x n = b 2.

a 11 x 1 + a 12 x 2 + + a 1n x n = b 1 a 21 x 1 + a 22 x 2 + + a 2n x n = b 2. Chapter 1 LINEAR EQUATIONS 1.1 Introduction to linear equations A linear equation in n unknowns x 1, x,, x n is an equation of the form a 1 x 1 + a x + + a n x n = b, where a 1, a,..., a n, b are given

More information

Full and Complete Binary Trees

Full and Complete Binary Trees Full and Complete Binary Trees Binary Tree Theorems 1 Here are two important types of binary trees. Note that the definitions, while similar, are logically independent. Definition: a binary tree T is full

More information

Solution to Exercise 2.2. Both m and n are divisible by d, som = dk and n = dk. Thus m ± n = dk ± dk = d(k ± k ),som + n and m n are divisible by d.

Solution to Exercise 2.2. Both m and n are divisible by d, som = dk and n = dk. Thus m ± n = dk ± dk = d(k ± k ),som + n and m n are divisible by d. [Chap. ] Pythagorean Triples 6 (b) The table suggests that in every primitive Pythagorean triple, exactly one of a, b,orc is a multiple of 5. To verify this, we use the Pythagorean Triples Theorem to write

More information

3 0 + 4 + 3 1 + 1 + 3 9 + 6 + 3 0 + 1 + 3 0 + 1 + 3 2 mod 10 = 4 + 3 + 1 + 27 + 6 + 1 + 1 + 6 mod 10 = 49 mod 10 = 9.

3 0 + 4 + 3 1 + 1 + 3 9 + 6 + 3 0 + 1 + 3 0 + 1 + 3 2 mod 10 = 4 + 3 + 1 + 27 + 6 + 1 + 1 + 6 mod 10 = 49 mod 10 = 9. SOLUTIONS TO HOMEWORK 2 - MATH 170, SUMMER SESSION I (2012) (1) (Exercise 11, Page 107) Which of the following is the correct UPC for Progresso minestrone soup? Show why the other numbers are not valid

More information

The Taxman Game. Robert K. Moniot September 5, 2003

The Taxman Game. Robert K. Moniot September 5, 2003 The Taxman Game Robert K. Moniot September 5, 2003 1 Introduction Want to know how to beat the taxman? Legally, that is? Read on, and we will explore this cute little mathematical game. The taxman game

More information

WRITING PROOFS. Christopher Heil Georgia Institute of Technology

WRITING PROOFS. Christopher Heil Georgia Institute of Technology WRITING PROOFS Christopher Heil Georgia Institute of Technology A theorem is just a statement of fact A proof of the theorem is a logical explanation of why the theorem is true Many theorems have this

More information

Math Games For Skills and Concepts

Math Games For Skills and Concepts Math Games p.1 Math Games For Skills and Concepts Original material 2001-2006, John Golden, GVSU permission granted for educational use Other material copyright: Investigations in Number, Data and Space,

More information