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



Similar documents
Definition and Calculus of Probability

Feb 7 Homework Solutions Math 151, Winter Chapter 4 Problems (pages )

Fundamentele Informatica II

Homework 3 (due Tuesday, October 13)

Statistics 100A Homework 3 Solutions

WORKED EXAMPLES 1 TOTAL PROBABILITY AND BAYES THEOREM

Homework 3 Solution, due July 16

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

2 GENETIC DATA ANALYSIS

Probabilistic Strategies: Solutions

6.3 Conditional Probability and Independence

WHERE DOES THE 10% CONDITION COME FROM?

Chapter 4 Lecture Notes

Math 3C Homework 3 Solutions

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

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

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

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

Basic Probability Concepts

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

Statistics 100A Homework 2 Solutions

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

Solutions for Practice problems on proofs

Math Quizzes Winter 2009

Variations on a Human Face Lab

36 Odds, Expected Value, and Conditional Probability

Math 55: Discrete Mathematics

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

Statistics 100A Homework 4 Solutions

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

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

AP Stats - Probability Review

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

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

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

Math 319 Problem Set #3 Solution 21 February 2002

Bayesian Tutorial (Sheet Updated 20 March)

Bayesian Nash Equilibrium

Genetics for the Novice

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

Sample Induction Proofs

AN ANALYSIS OF A WAR-LIKE CARD GAME. Introduction

3.2 Roulette and Markov Chains

Lecture 13. Understanding Probability and Long-Term Expectations

Probability and Expected Value

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

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

Section 6-5 Sample Spaces and Probability

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

Mathematical goals. Starting points. Materials required. Time needed

Week 2: Conditional Probability and Bayes formula

A Few Basics of Probability

DNA Determines Your Appearance!

Current California Math Standards Balanced Equations

Estimating Probability Distributions

Chapter 5. Discrete Probability Distributions

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

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

Ch. 13.2: Mathematical Expectation

1 Gambler s Ruin Problem

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

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

Math 115 Spring 2011 Written Homework 5 Solutions

Fundamentals of Probability

ST 371 (IV): Discrete Random Variables

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

DOUBLES TENNIS LEAGUE

Additional Probability Problems

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

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

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

E3: PROBABILITY AND STATISTICS lecture notes

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

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

Colored Hats and Logic Puzzles

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

Binomial lattice model for stock prices

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

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.

SECTION 10-5 Multiplication Principle, Permutations, and Combinations

4. Continuous Random Variables, the Pareto and Normal Distributions

arxiv: v1 [math.pr] 5 Dec 2011

Regular Languages and Finite State Machines

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

Section 5-3 Binomial Probability Distributions

C H A P T E R Regular Expressions regular expression

Introduction to Hypothesis Testing

Tiers, Preference Similarity, and the Limits on Stable Partners

Genetics with a Smile

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

Elements of probability theory

Section 7C: The Law of Large Numbers

SCORE SETS IN ORIENTED GRAPHS

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

Full and Complete Binary Trees

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.

mod 10 = mod 10 = 49 mod 10 = 9.

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

WRITING PROOFS. Christopher Heil Georgia Institute of Technology

Math Games For Skills and Concepts

Transcription:

Jan 31 Homework Solutions Math 151, Winter 01 Chapter 3 Problems (pages 10-110) 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

Thus P (offspring is aa) P (offspring is aa both parents are Aa)P (both parents are Aa) 1 4 3 1 6. (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) 1 1 6 5 6 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 ) 4 3 1 8. 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 5/6 3 0. 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.

(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

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) 1 3 4 1 3 4 1 9 18. 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) 1 1 1 1 1 1 3. (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) 1 3 4 1 3 4 1 9 18. P (matches nd parent s genotype) P (A correct)p (B correct)p (C correct)p (D correct)p (E correct) 1 1 1 1 1 1 3. (c) either parent? 4

P (matches either parent s phenotype) P (matches 1st parent s phenotype) + P (matches nd parent s phenotype) 9 64. 9 18 + 9 18 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 1 3 + 1 3 1 16. (d) neither parent? P (matches neither parent s phenotype) 1 P (matches either parent s phenotype) 1 9 64 55 64. P (matches neither parent s genotype) 1 P (matches either parent s genotype) 1 1 16 15 16. 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

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

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 1 1 (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

(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 ) 3 4 + P n 1 4 P (E F )P (F ) + P (E F c )P (F c ) 1 0 n 1 + 4 + P ) n 1 n 4 n 1 4 + 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 1 1 1 n 1 1 1 1 1 1 1 0 For the inductive step, suppose that formula P n 1 1 1 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

we have P n 4 + P ) n 1 n 4 n 1 4 + 1 1 ) n 4 4 + 1 4 1 ) 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 1 1 1 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

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 40 1. 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+1.55 + P n 1.45. 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+1.55 + P n 1.45.45(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 10 0. To compute P 11, note that 1 P 40 P 10 39 n10 (P n+1 P n ) 39 n10 (.45/.55) n 10 P 11 1 (.45/.55)30 1.45/.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 11 1.45/.55 1 (.45/.55) 30. 4 n10 4 (P n+1 P n ) (.45/.55) n 10 P 11 n10 1 (.45/.55)15 1.45/.55 P 11 1 (.45/.55)15 1.45/.55 1 (.45/.55)15 1 (.45/.55) 30 0.9530. 1.45/.55 1 (.45/.55) 30 10

Chapter 3 Theoretical Exercises (pages 110-113) 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

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 17-179) 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 ).1758 1

( ) 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