Discrete Mathematics and Its Applicationsdase.ecnu.edu.cn/mgao/teaching/DM_2020_Spring/slides/3_counting… · Indistinguishable Objects and Indistinguishable Boxes 7 Generating Permutations

Discrete Mathematics and Its ApplicationsLecture 3: Counting Principles

MING GAO

DaSE@ ECNU(for course related communications)

[email protected]

Apr. 7, 2020

Outline

1 Counting Principle

2 Permutations

3 Division Rule

4 Combinations

5 Subtraction rulePermutations with Indistinguishable Objects

6 Distributing Objects into BoxesDistinguishable Objects and Distinguishable BoxesIndistinguishable Objects and Distinguishable BoxesDistinguishable Objects and Indistinguishable BoxesIndistinguishable Objects and Indistinguishable Boxes

7 Generating Permutations and Combinations

8 Take-aways

MING GAO (DaSE@ECNU) Discrete Mathematics and Its Applications Apr. 7, 2020 2 / 62

Counting Principle

Let’s count

How many lunches can you have?

A snack bar serves five different sandwiches and three different bev-erages. How many different lunches can a person order?

Solution

1 One way of determining the number of possible lunches is by listing orenumerating all the possibilities;

2 One systematic way of doing this is by means of a tree;

3 Counting elements in a cartesian product. A listing of possiblelunches a person could have is:

A× B = {(Beef ; milk), (Beef ; juice), · · · , (Bologna; coffee)},

where A = {beef , ham, chicken, cheese, bologna}, and B ={milk, juice, coffee}.


Counting Principle

Let’s count


A snack bar serves five different sandwiches and three different bev-erages. How many different lunches can a person order?

Solution

1 One way of determining the number of possible lunches is by listing orenumerating all the possibilities;

2 One systematic way of doing this is by means of a tree;

3 Counting elements in a cartesian product. A listing of possiblelunches a person could have is:

A× B = {(Beef ; milk), (Beef ; juice), · · · , (Bologna; coffee)},

where A = {beef , ham, chicken, cheese, bologna}, and B ={milk, juice, coffee}.


Counting Principle

Counting principle

Product rule

Suppose that a procedure consists of a sequence of two tasks. Ifthere are n1 ways to do the first task, there are n2 ways to do thesecond task, then there are n1n2 ways to do the procedure.

Extended version: A procedure is followed by tasks T1,T2, · · · ,Tm insequence. If each task Ti can be done in ni ways independently, then thereare n1 · n2 · · · · · nm ways to carry out the procedure.

Sum rule

If a task can be done either in one of n1 ways or in one of n2 ways,where none of the set of n1 ways is the same as any of the set of n2

ways, then there are n1 + n2 ways to do the task.

Extended version: A procedure can be done by m ways, each way Wi hasni possibilities (not intersect), then there are n1 + n2 + · · ·+ nm ways tocarry out the procedure.


Counting Principle

Counting principle

Product rule



Sum rule





Counting Principle

Counting principle

Product rule



Sum rule





Counting Principle

Counting principle

Product rule



Sum rule





Counting Principle


Solution

1 Product rule:Task Number

Task 1: Choose sandwich 5Task 2: Choose beverage 3

Therefore, there are 5× 3 = 15 ways to order lunches.

2 Sum rule:Way of first order NumberWay 1: beef 3Way 2: ham 3Way 3: chicken 3Way 4: cheese 3Way 5: beef 3

Therefore, there are 3 + 3 + 3 + 3 + 3 = 15 ways to orderlunches.


Counting Principle


Solution

1 Product rule:Task NumberTask 1: Choose sandwich 5Task 2: Choose beverage 3





Counting Principle


Solution



2 Sum rule:Way of first order Number

Way 1: beef 3Way 2: ham 3Way 3: chicken 3Way 4: cheese 3Way 5: beef 3



Counting Principle


Solution






Counting Principle

Counting functions

Solution

How many functions are there from set A with m elements to set Bwith n elements?

A function corresponds to a choice of one of n elements in codomainB for each of m elements in domain A.In terms of the product rule:

Task NumberTask 1: a1 ∈ A nTask 2: a2 ∈ A n

· · ·Task m: am ∈ A n

Therefore, there are n · n · · · · · n︸︷︷︸m times

= nm functions.


Counting Principle

Counting functions

Solution

How many functions are there from set A with m elements to set Bwith n elements?A function corresponds to a choice of one of n elements in codomainB for each of m elements in domain A.

In terms of the product rule:Task NumberTask 1: a1 ∈ A nTask 2: a2 ∈ A n



= nm functions.


Counting Principle

Counting functions

Solution

How many functions are there from set A with m elements to set Bwith n elements?A function corresponds to a choice of one of n elements in codomainB for each of m elements in domain A.In terms of the product rule:

Task Number

Task 1: a1 ∈ A nTask 2: a2 ∈ A n



= nm functions.


Counting Principle

Counting functions

Solution

How many functions are there from set A with m elements to set Bwith n elements?A function corresponds to a choice of one of n elements in codomainB for each of m elements in domain A.In terms of the product rule:

Task NumberTask 1: a1 ∈ A nTask 2: a2 ∈ A n



= nm functions.


Counting Principle

Application of counting functions

1 A is a finite set, then |P(A)| = 2|A|.

2 How many different bit strings of length seven are there? Howmany bit strings of length seven both begin and end with a 1?

3 A person is to complete a true-false questionnaire consisting often questions. How many different ways are there to answerthe questionnaire?

4 How many different license plates can be made if each platecontains a sequence of three uppercase English letters followedby three digits (and no sequences of letters are prohibited, evenif they are obscene)?


Counting Principle

Examples

Solution

How many strings are there of four lowercase letters that have letterx in them?

In terms of the sum and product rules:Task NumberWay 1: contain 1 x 4× 253

Task 11: choose location of x 4Task 12: fill the remaining location 253

Way 2: contain 2 x 6× 252

Task 21: choose locations of x 6Task 22: fill the remaining location 252

Way 3: contain 3 x 4× 25Task 31: choose locations of x 4Task 32: fill the remaining location 25

Way 4: contain 4 x 1

Therefore, there are 4× 253 + 6× 252 + 4× 25 + 1 functions.


Counting Principle

Examples

Solution

How many strings are there of four lowercase letters that have letterx in them? In terms of the sum and product rules:

Task NumberWay 1: contain 1 x 4× 253








Counting Principle

Examples

Solution


Task Number









Counting Principle

Examples

Solution










Counting Principle

Examples

Solution










Counting Principle

Examples

Solution










Counting Principle

Examples

Solution










Counting Principle

Counting one-to-one functions

Solution

How many one-to-one functions are there from a set with m elementsto one with n elements?

Is there one-to-one functions from set A to B if m > n?

Now let m ≤ n. Suppose the elements in the domain area1, a2, · · · , am ∈ A.In terms of the product rule:

Task NumberTask 1: a1 ∈ A nTask 2: a2 ∈ A n − 1

· · ·Task m: am ∈ A n −m + 1

Therefore, there are n · (n − 1) · · · · · (n + m − 1)︸︷︷︸m times

functions.


Counting Principle


Solution





· · ·Task m: am ∈ A n −m + 1


functions.


Counting Principle


Solution



Now let m ≤ n. Suppose the elements in the domain area1, a2, · · · , am ∈ A.

In terms of the product rule:Task NumberTask 1: a1 ∈ A nTask 2: a2 ∈ A n − 1

· · ·Task m: am ∈ A n −m + 1


functions.


Counting Principle


Solution




Task Number

Task 1: a1 ∈ A nTask 2: a2 ∈ A n − 1

· · ·Task m: am ∈ A n −m + 1


functions.


Counting Principle


Solution





· · ·Task m: am ∈ A n −m + 1


functions.


Permutations

Permutations

Definition

A permutation of a set of distinct objects is an ordered arrangement ofthese objects. An ordered arrangement of m elements of a set is called anm-permutation.

Examples

1 How many ways are there to select a first-prize winner, asecond-prize winner, and a third-prize winner from 100different people who have entered a contest?

2 A saleswoman has to visit eight different cities. She mustbegin her trip in a specified city, but she can visit the otherseven cities in any order she wishes. How many possible orderscan the saleswoman use when visiting these cities?


Permutations

Permutations

Definition

A permutation of a set of distinct objects is an ordered arrangement ofthese objects. An ordered arrangement of m elements of a set is called anm-permutation.

Examples

1 How many ways are there to select a first-prize winner, asecond-prize winner, and a third-prize winner from 100different people who have entered a contest?

2 A saleswoman has to visit eight different cities. She mustbegin her trip in a specified city, but she can visit the otherseven cities in any order she wishes. How many possible orderscan the saleswoman use when visiting these cities?


Permutations

The number of permutations

Theorem

If n is a positive integer and m is an integer with 1 ≤ m ≤ n, then there are

P(n,m) = n(n − 1)(n − 2) · · · · · (n −m + 1),

m-permutations of a set with n distinct elements.

Proof.

In terms of the product rule:Task Number

Task 1: a1 ∈ A nTask 2: a2 ∈ A n − 1

· · ·Task m: am ∈ A n −m + 1


functions.


Permutations

The number of permutations

Theorem

If n is a positive integer and m is an integer with 1 ≤ m ≤ n, then there are

P(n,m) = n(n − 1)(n − 2) · · · · · (n −m + 1),

m-permutations of a set with n distinct elements.

Proof.

In terms of the product rule:Task NumberTask 1: a1 ∈ A nTask 2: a2 ∈ A n − 1

· · ·Task m: am ∈ A n −m + 1


functions.


Permutations

Number of permutations cont’d

If n and m are integers with 0 ≤ m ≤ n, then

P(n,m) =n!

(n −m)!.

We have proved this corollary.

Corollary: The number of permutations of a set with n elements isn!.

Remark: 0! = 1, and 1! = 1.

Abbreviations: We shall call a set with n elements as an n-set.We shall call a subset with k elements as a k-subset. In general,elements in a given set is unordered. I.e., sets {1, 2, 3} and {3, 1, 2}are the same set.However, sometimes, it is useful to treat sets as ordered.


Permutations



P(n,m) =n!

(n −m)!.



Remark: 0! = 1, and 1! = 1.



Permutations



P(n,m) =n!

(n −m)!.



Remark: 0! = 1, and 1! = 1.

Abbreviations: We shall call a set with n elements as an n-set.We shall call a subset with k elements as a k-subset. In general,elements in a given set is unordered. I.e., sets {1, 2, 3} and {3, 1, 2}are the same set.

However, sometimes, it is useful to treat sets as ordered.


Permutations



P(n,m) =n!

(n −m)!.



Remark: 0! = 1, and 1! = 1.



Permutations

Example: runners

Question: There are 10 runners for a given competition. There are3 awards: 1st price, 2nd price and 3rd price. In how many possibleways these 3 awards can be given? (No runner can get more thanone award.)

We can use the argument we used to derive the number of permutationshere. We consider the process for selecting the winners.

First, we pick the 1st price winner: there are 10 choices.

For any 1st price winner, there are 9 choices to choose the 2nd pricewinner.

For any 1st and 2nd price winners, there are 8 choices for the 3rdwinner.

Therefore, we conclude that the number of ways is 10 · 9 · 8.


Permutations

Example: runners








Permutations

Example: runners








Permutations

Example: runners








Permutations

Example: runners








Permutations

Example: runners








Permutations

Example: runners (another look)

We can arrive at the same answer by a different way of counting.

Let’s count all possible running results: there are 10! results. (I.e.,each running result is a permutation.)

10! is too many for our answer. Why?

For a particular selection of 3 top winners, how many possible runningresults have exactly these 3 top winners?

The number of running results is the number of permutation of theother 7 non-winning runners; thus, there are 7! of them.

We can think of a process of choosing a permutation as having twobig steps: (1) pick 3 top winners, then (2) pick the rest of runners.This provide a different way to count the number of permutations.

Let X be the set of ordered subsets with 3 elements of an 10-set. Wethen have |X | × 7! = 10!, because they count the same objects.Solving this yields

|X | =10!

7!= 10 · 9 · 8.


Permutations









|X | =10!

7!= 10 · 9 · 8.


Permutations









|X | =10!

7!= 10 · 9 · 8.


Permutations









|X | =10!

7!= 10 · 9 · 8.


Permutations








Let X be the set of ordered subsets with 3 elements of an 10-set. Wethen have |X | × 7! = 10!, because they count the same objects.

Solving this yields

|X | =10!

7!= 10 · 9 · 8.


Permutations









|X | =10!

7!= 10 · 9 · 8.


Permutations

How big is 100! ?

With computers, we may be able to answer the exact long number.But mathematicians usually enjoy a “quick” estimate just to have arough idea on how things are.

How can we start?

When we want to get an estimate, we usuallystart by finding an upper bound and a lower bound for the quantity.As the names suggest, the upper bound for x is a quantity that is notsmaller than x , and the lower bound for x is a quantity that is notlarger than x (maybe under some conditions).

Let’s think about n!.

The first lower bound that comes to mind for n! is 1n = 1.Can we get a better lower bound? (Here, better lower bounds shouldbe closer to the actual value.) How about 2n? Is it a lower bound?How about 3n or 5n? Are they lower bounds of n!?


Permutations

How big is 100! ?


How can we start? When we want to get an estimate, we usuallystart by finding an upper bound and a lower bound for the quantity.

As the names suggest, the upper bound for x is a quantity that is notsmaller than x , and the lower bound for x is a quantity that is notlarger than x (maybe under some conditions).




Permutations

How big is 100! ?


How can we start? When we want to get an estimate, we usuallystart by finding an upper bound and a lower bound for the quantity.As the names suggest, the upper bound for x is a quantity that is notsmaller than x , and the lower bound for x is a quantity that is notlarger than x (maybe under some conditions).




Permutations

How big is 100! ?






Permutations

How big is 100! ?




The first lower bound that comes to mind for n! is 1n = 1.

Can we get a better lower bound? (Here, better lower bounds shouldbe closer to the actual value.) How about 2n? Is it a lower bound?How about 3n or 5n? Are they lower bounds of n!?


Permutations

How big is 100! ?




The first lower bound that comes to mind for n! is 1n = 1.Can we get a better lower bound? (Here, better lower bounds shouldbe closer to the actual value.)

How about 2n? Is it a lower bound?How about 3n or 5n? Are they lower bounds of n!?


Permutations

How big is 100! ?




The first lower bound that comes to mind for n! is 1n = 1.Can we get a better lower bound? (Here, better lower bounds shouldbe closer to the actual value.) How about 2n? Is it a lower bound?

How about 3n or 5n? Are they lower bounds of n!?


Permutations

How big is 100! ?






Permutations

Bounds for n!

Recall that n! = 1 · 2 · 3 · · · n. Since all its factor, except the first one is atleast 2, we have that

2n−1 ≤ n!.

Similarly, since all factors of n! is at most n, we have that

n! ≤ nn.

A slightly better upper bound is nn−1 because we can, again, ignore 1.

Are they any good?n 2n−1 n! nn−1

1 1 1 12 2 2 23 4 6 94 8 24 64

10 512 3, 628, 800 1, 000, 000, 000


Permutations

Bounds for n!


2n−1 ≤ n!.


n! ≤ nn.



1 1 1 12 2 2 23 4 6 94 8 24 64

10 512 3, 628, 800 1, 000, 000, 000


Permutations

Bounds for n!


2n−1 ≤ n!.


n! ≤ nn.



1 1 1 12 2 2 23 4 6 94 8 24 64

10 512 3, 628, 800 1, 000, 000, 000


Permutations

Bounds for n!


2n−1 ≤ n!.


n! ≤ nn.


Are they any good?

n 2n−1 n! nn−1

1 1 1 12 2 2 23 4 6 94 8 24 64

10 512 3, 628, 800 1, 000, 000, 000


Permutations

Bounds for n!


2n−1 ≤ n!.


n! ≤ nn.



1 1 1 12 2 2 23 4 6 94 8 24 64

10 512 3, 628, 800 1, 000, 000, 000


Permutations

A better bound?

Let’s consider n! again, but for simplicity, let’s consider only the case whenn is an even number:

1 · 2 · 3 · · · (n/2− 1) · (n/2) · (n/2 + 1) · · · n

To get a better lower bound, we may move our cutting point from 2 to,say, n/2. Note that at least n/2 factors are at least n/2. Thus,

n! = 1 · 2 · · · n≥ 1 · 1 · · · 1︸︷︷︸

n/2

× (n/2) · · · (n/2)︸︷︷︸n/2

= (n/2)n/2 =√

(n/2)n.


Permutations

A better bound?

Let’s consider n! again, but for simplicity, let’s consider only the case whenn is an even number:

1 · 2 · 3 · · · (n/2− 1) · (n/2) · (n/2 + 1) · · · n

To get a better lower bound, we may move our cutting point from 2 to,say, n/2. Note that at least n/2 factors are at least n/2. Thus,

n! = 1 · 2 · · · n≥ 1 · 1 · · · 1︸︷︷︸

n/2

× (n/2) · · · (n/2)︸︷︷︸n/2

= (n/2)n/2 =√

(n/2)n.


Permutations

Better?

n 2n−1√

(n/2)n n! nn−1

1 1 - 1 12 2 1 2 23 4 - 6 94 8 4 24 646 32 27 720 7, 776

10 512 3, 125 3, 628, 800 1, 000, 000, 00012 2, 048 46, 656 479, 001, 600 743, 008, 370, 688

OK. A bit better.


Permutations

Stirling’s formula

Theorem

Theorem (Stirling’s formula)

n! ∼(ne

)n√2πn.

When we write a(n) ∼ b(n), we mean that a(n)b(n) → 1 as n→∞.

With Stirling’s formula, We can use a calculator to estimate the number ofdigits for 100!. The estimate for 100! is

(100/e)100 ·√

200π

Thus, the number of digits is its logarithm, in base 10, i.e.,

log(

(100/e)100 ·√

200π)

= 100 log(100/e) + log(200π) ≈ 157.9696.

Note that the correct answer is 158 digits.


Permutations


Theorem


n! ∼(ne

)n√2πn.


With Stirling’s formula, We can use a calculator to estimate the number ofdigits for 100!.

The estimate for 100! is

(100/e)100 ·√

200π


log(

(100/e)100 ·√

200π)

= 100 log(100/e) + log(200π) ≈ 157.9696.



Permutations


Theorem


n! ∼(ne

)n√2πn.



(100/e)100 ·√

200π


log(

(100/e)100 ·√

200π)

= 100 log(100/e) + log(200π) ≈ 157.9696.



Permutations


Theorem


n! ∼(ne

)n√2πn.



(100/e)100 ·√

200π


log(

(100/e)100 ·√

200π)

= 100 log(100/e) + log(200π) ≈ 157.9696.

Note that the correct answer is 158 digits.MING GAO (DaSE@ECNU) Discrete Mathematics and Its Applications Apr. 7, 2020 19 / 62

Division Rule

Division rule

Subtraction rule

There are n/d ways to do a task if it can be done using a procedurethat can be carried out in n ways, and for every way w , exactly d ofthe n ways correspond to way w .

Recap

Question: How many different committees of three students can beformed from a group of ten students?Solution: We obtain P(10, 3) ordered 3−subsets. However, for agiven ordered 3−subsets (e.g., {1, 2, 3}), there are P(3, 3) replicatesfor the group of committee members {1, 2, 3}.Therefore, total number of groups of committees is P(10,3)

P(3,3) =(103

).


Division Rule

Example

The problem of seating around a circular table

Question: How many different ways are there to seat four peoplearound a circular table, where two seatings are considered the samewhen each person has the same left neighbor and the same rightneighbor?

Solution: We arbitrarily select a seat at the table and label it seat1. We number the rest of the seats in numerical order, proceedingclockwise around the table.Note that there are 4! = 24 ways to order the given four people forthese seats in a line.However, each of the four choices for seat 1 leads to the same ar-rangement in a circle, as we distinguish two arrangements only whena person has a different immediate left or immediate right neighbor.By the division rule, there are 24/4 = 6 different seating arrange-ments of four people around the circular table.


Division Rule

Example


Question: How many different ways are there to seat four peoplearound a circular table, where two seatings are considered the samewhen each person has the same left neighbor and the same rightneighbor?Solution: We arbitrarily select a seat at the table and label it seat1. We number the rest of the seats in numerical order, proceedingclockwise around the table.

Note that there are 4! = 24 ways to order the given four people forthese seats in a line.However, each of the four choices for seat 1 leads to the same ar-rangement in a circle, as we distinguish two arrangements only whena person has a different immediate left or immediate right neighbor.By the division rule, there are 24/4 = 6 different seating arrange-ments of four people around the circular table.


Division Rule

Example


Question: How many different ways are there to seat four peoplearound a circular table, where two seatings are considered the samewhen each person has the same left neighbor and the same rightneighbor?Solution: We arbitrarily select a seat at the table and label it seat1. We number the rest of the seats in numerical order, proceedingclockwise around the table.Note that there are 4! = 24 ways to order the given four people forthese seats in a line.

However, each of the four choices for seat 1 leads to the same ar-rangement in a circle, as we distinguish two arrangements only whena person has a different immediate left or immediate right neighbor.By the division rule, there are 24/4 = 6 different seating arrange-ments of four people around the circular table.


Division Rule

Example


Question: How many different ways are there to seat four peoplearound a circular table, where two seatings are considered the samewhen each person has the same left neighbor and the same rightneighbor?Solution: We arbitrarily select a seat at the table and label it seat1. We number the rest of the seats in numerical order, proceedingclockwise around the table.Note that there are 4! = 24 ways to order the given four people forthese seats in a line.However, each of the four choices for seat 1 leads to the same ar-rangement in a circle, as we distinguish two arrangements only whena person has a different immediate left or immediate right neighbor.

By the division rule, there are 24/4 = 6 different seating arrange-ments of four people around the circular table.


Division Rule

Example


Question: How many different ways are there to seat four peoplearound a circular table, where two seatings are considered the samewhen each person has the same left neighbor and the same rightneighbor?Solution: We arbitrarily select a seat at the table and label it seat1. We number the rest of the seats in numerical order, proceedingclockwise around the table.Note that there are 4! = 24 ways to order the given four people forthese seats in a line.However, each of the four choices for seat 1 leads to the same ar-rangement in a circle, as we distinguish two arrangements only whena person has a different immediate left or immediate right neighbor.By the division rule, there are 24/4 = 6 different seating arrange-ments of four people around the circular table.


Combinations

Example: committee members

Question: How many different committees of three students can beformed from a group of ten students?

Is the number of P(10, 3) is correct? Why?

A group of committees

For student 1, 2, and 3. Ordered sets

{1, 2, 3}, {1, 3, 2}, {2, 1, 3}, {2, 3, 1}, {3, 1, 2}, {3, 1, 2}

are the same group of committees. Remember that the number ofthe ordered sets is .The number of different groups of committees should be

P(10, 3)

P(3, 3).


Combinations






{1, 2, 3}, {1, 3, 2}, {2, 1, 3}, {2, 3, 1}, {3, 1, 2}, {3, 1, 2}


P(10, 3)

P(3, 3).


Combinations






{1, 2, 3}, {1, 3, 2}, {2, 1, 3}, {2, 3, 1}, {3, 1, 2}, {3, 1, 2}

are the same group of committees. Remember that the number ofthe ordered sets is .

The number of different groups of committees should be

P(10, 3)

P(3, 3).


Combinations






{1, 2, 3}, {1, 3, 2}, {2, 1, 3}, {2, 3, 1}, {3, 1, 2}, {3, 1, 2}


P(10, 3)

P(3, 3).


Combinations

Combinations

Definition

An m-combination of elements of a set is an unordered selection of melements from the set.

Theorem: The number of m-combinations of a set with n elements,where n is a nonnegative integer and m is an integer with 0 ≤ m ≤ n,equals

C (n,m) =n!

m!(n −m)!,

where C (n,m) is also denoted as(nm

).

Corollary: The number of m-subsets of an n-set is

C (n,m) =n · (n − 1) · (n − 2) · · · (n −m + 1)

m!=

n!

(n −m)!m!.


Combinations

Combinations

Definition



C (n,m) =n!

m!(n −m)!,


).


C (n,m) =n · (n − 1) · (n − 2) · · · (n −m + 1)

m!=

n!

(n −m)!m!.


Combinations

Combinations

Definition



C (n,m) =n!

m!(n −m)!,


).


C (n,m) =n · (n − 1) · (n − 2) · · · (n −m + 1)

m!=

n!

(n −m)!m!.


Combinations

Corollary proof

Proof.

Consider the following process for choosing an ordered subsets with kelements of an n-set.

First, we choose a k-subset, then we permute it. LetB be the number of k-subsets. For each subset that we choose in the firststep, the second step has k! choices. Therefore, we can choose an orderedsubset in B · k! possible ways. From the previous discussion, we know that

B · k! = n · (n − 1) · · · (n − k + 1).

Therefore, the number of k-subsets is

n · (n − 1) · (n − 2) · · · (n − k + 1)

k!=

n!

(n − k)!k!,

as required.


Combinations

Corollary proof

Proof.

Consider the following process for choosing an ordered subsets with kelements of an n-set. First, we choose a k-subset, then we permute it. LetB be the number of k-subsets. For each subset that we choose in the firststep, the second step has k! choices.

Therefore, we can choose an orderedsubset in B · k! possible ways. From the previous discussion, we know that

B · k! = n · (n − 1) · · · (n − k + 1).


n · (n − 1) · (n − 2) · · · (n − k + 1)

k!=

n!

(n − k)!k!,

as required.


Combinations

Corollary proof

Proof.

Consider the following process for choosing an ordered subsets with kelements of an n-set. First, we choose a k-subset, then we permute it. LetB be the number of k-subsets. For each subset that we choose in the firststep, the second step has k! choices. Therefore, we can choose an orderedsubset in B · k! possible ways.

From the previous discussion, we know that

B · k! = n · (n − 1) · · · (n − k + 1).


n · (n − 1) · (n − 2) · · · (n − k + 1)

k!=

n!

(n − k)!k!,

as required.


Combinations

Corollary proof

Proof.

Consider the following process for choosing an ordered subsets with kelements of an n-set. First, we choose a k-subset, then we permute it. LetB be the number of k-subsets. For each subset that we choose in the firststep, the second step has k! choices. Therefore, we can choose an orderedsubset in B · k! possible ways. From the previous discussion, we know that

B · k! = n · (n − 1) · · · (n − k + 1).


n · (n − 1) · (n − 2) · · · (n − k + 1)

k!=

n!

(n − k)!k!,

as required.


Combinations

Examples of combinations

Applications

1 How many poker hands of five cards can be dealt from astandard deck of 52 cards? Also, how many ways are there toselect 47 cards from a standard deck of 52 cards?

2 How many ways are there to select five players from a10-member tennis team to make a trip to a match at anotherschool?

3 A group of 30 people have been trained as astronauts to go onthe first mission to Mars. How many ways are there to select acrew of six people to go on this mission?


Combinations

Binomial coefficients

The number of k-subsets of an n-set is very useful. Hence, there is anotation for it, i.e., (

n

k

)=

n!

(n − k)!k!,

(which reads “n choose k”). These numbers are called binomialcoefficients.

Note that(nn

)= 1 (why?),(n

0

)= 1 (why?), and,

when k > n,(nk

)= 0.


Combinations



n

k

)=

n!

(n − k)!k!,


Note that(nn

)= 1 (why?),

(n0

)= 1 (why?), and,

when k > n,(nk

)= 0.


Combinations



n

k

)=

n!

(n − k)!k!,


Note that(nn

)= 1 (why?),(n

0

)= 1 (why?),

and,

when k > n,(nk

)= 0.


Combinations



n

k

)=

n!

(n − k)!k!,


Note that(nn

)= 1 (why?),(n

0

)= 1 (why?), and,

when k > n,(nk

)= 0.


Combinations

Example

The coefficient of a polynomial

Question: What is the coefficient of x2 in polynomial (x2+3x +1)5?

Solution:Way To do CoefficientWay 1: a x2 and four 1 C (5, 1)C (4, 4)x2 · 14

Task 11: select a x2 C (5, 1)x2

Task 12: select four 1 C (4, 4)14

Way 2: two x and three 1 C (5, 2)C (3, 3)(3x)2 · 13Task 21: select two x2 C (5, 2)(3x)2

Task 22: select three 1 C (3, 3)13

Therefore, the coefficient of x2 in the polynomial is 95.


Combinations

Example


Question: What is the coefficient of x2 in polynomial (x2+3x +1)5?Solution:

Way To do Coefficient

Way 1: a x2 and four 1 C (5, 1)C (4, 4)x2 · 14Task 11: select a x2 C (5, 1)x2






Combinations

Example


Question: What is the coefficient of x2 in polynomial (x2+3x +1)5?Solution:

Way To do CoefficientWay 1: a x2 and four 1 C (5, 1)C (4, 4)x2 · 14

Task 11: select a x2 C (5, 1)x2






Combinations

Combinations with repetition


Question: How many ways are there to select five bills from a cashbox containing $1 bills, $2 bills, $5 bills, $10 bills, $20 bills, $50 bills,and $100 bills? Assume that the order in which the bills are chosendoes not matter, that the bills of each denomination are indistin-guishable, and that there are at least five bills of each type.

Solution:

Therefore, it corresponds to the number of unordered selections of 5objects from a set of 11 objects, which can be done in C (11, 5) ways.


Combinations



Question: How many ways are there to select five bills from a cashbox containing $1 bills, $2 bills, $5 bills, $10 bills, $20 bills, $50 bills,and $100 bills? Assume that the order in which the bills are chosendoes not matter, that the bills of each denomination are indistin-guishable, and that there are at least five bills of each type.Solution:



Combinations



Question: How many ways are there to select five bills from a cashbox containing $1 bills, $2 bills, $5 bills, $10 bills, $20 bills, $50 bills,and $100 bills? Assume that the order in which the bills are chosendoes not matter, that the bills of each denomination are indistin-guishable, and that there are at least five bills of each type.Solution:



Combinations

Generalization

Theorem: There are C (n + r − 1, r) = C (n + r − 1, n − 1) r -combinations from a set with n elements when repetition of elementsis allowed.

Examples

Suppose that a cookie shop has four different kinds of cookies.How many different ways can six cookies be chosen? Assumethat only the type of cookie, and not the individual cookies orthe order in which they are chosen, matters.

How many solutions does the equation x1 + x2 + x3 = 11 have,where x1, x2, and x3 are nonnegative integers?(C (11 + 3− 1, 11) = C (11 + 3− 1, 3− 1))


Combinations

Generalization

Theorem: There are C (n + r − 1, r) = C (n + r − 1, n − 1) r -combinations from a set with n elements when repetition of elementsis allowed.

Examples

Suppose that a cookie shop has four different kinds of cookies.How many different ways can six cookies be chosen? Assumethat only the type of cookie, and not the individual cookies orthe order in which they are chosen, matters.

How many solutions does the equation x1 + x2 + x3 = 11 have,where x1, x2, and x3 are nonnegative integers?(C (11 + 3− 1, 11) = C (11 + 3− 1, 3− 1))


Subtraction rule

Subtraction rule

Subtraction rule

If a task can be done in either n1 ways or n2 ways, then the numberof ways to do the task is n1 + n2 minus the number of ways to dothe task that are common to the two different ways. The rule is alsocalled the principle of inclusion-exclusion, i.e.,

|A ∪ B| = |A|+ |B| − |A ∩ B|.

Application

Question: How many bit strings of length eight either start with a1 bit or end with two bits 00?Solution: Set A is bit strings of length eight start with a 1 bit;Set B is bit strings of length eight end with two bits 00;Therefore, |A ∪ B| = |A| + |B| − |A ∩ B| = 180, where |A| = 27,|B| = 26, and |A ∩ B| = 25.


Subtraction rule

Subtraction rule

Subtraction rule

If a task can be done in either n1 ways or n2 ways, then the numberof ways to do the task is n1 + n2 minus the number of ways to dothe task that are common to the two different ways. The rule is alsocalled the principle of inclusion-exclusion, i.e.,

|A ∪ B| = |A|+ |B| − |A ∩ B|.

Application

Question: How many bit strings of length eight either start with a1 bit or end with two bits 00?Solution: Set A is bit strings of length eight start with a 1 bit;Set B is bit strings of length eight end with two bits 00;Therefore, |A ∪ B| = |A| + |B| − |A ∩ B| = 180, where |A| = 27,|B| = 26, and |A ∩ B| = 25.


Subtraction rule

Quick questions (1)

There are 40 students in the classroom. There are 35 students wholike Naruto, 10 students who like Bleach, and 7 students who likeboth of them. How many students in this classroom who do not likeeither Bleach or Naruto?

A : the set of students who like Bleach;B : the set of students who like Naruto;The answer is

|A ∪ B| = 40− |A ∪ B| = 40− (35 + 10− 7) = 2.

Is this correct? Why?


Subtraction rule

Quick questions (2)

There are 35 students in the classroom. There are 25 students wholike Naruto, 15 students who like Bleach, 12 students who like OnePiece. There are 10 students who like both Naruto and Bleach, 7students who like both Bleach and One Piece, and 9 students wholike both Naruto and One Piece. There are 5 students who like all ofthem.How many students in this classroom who do not like any of Bleach,Naruto, or One Piece?


Subtraction rule

Is this correct?

The answer from the previous quick question is

35− (25 + 15 + 12− 10− 7− 9 + 5) = 4.


Let’s try to argue that this answer is, in fact, correct and try to findgeneral answers to this kind of counting questions.

Theorem: Let Ai be one of n sets, then

|n⋃

i=1

Ai | =n∑

k=1

(−1)k+1∑

1≤i1≤i2≤···≤ik≤n|Ai1 ∩ Ai2 ∩ · · · ∩ Aik |.

(called the Inclusion-Exclusion principle)


Subtraction rule

Is this correct?


35− (25 + 15 + 12− 10− 7− 9 + 5) = 4.




|n⋃

i=1

Ai | =n∑

k=1

(−1)k+1∑

1≤i1≤i2≤···≤ik≤n|Ai1 ∩ Ai2 ∩ · · · ∩ Aik |.



Subtraction rule

Is this correct?


35− (25 + 15 + 12− 10− 7− 9 + 5) = 4.




|n⋃

i=1

Ai | =n∑

k=1

(−1)k+1∑

1≤i1≤i2≤···≤ik≤n|Ai1 ∩ Ai2 ∩ · · · ∩ Aik |.



Subtraction rule

Let’s look at an individual student (1)

N B O NB BO NO NBO35 −25 −15 −12 +10 +7 +9 −5 4

Alfred N,O

* * * *Bobby B * *Cathy B,O * * * *Dave N,B,O * * * * * * * *Eddy - *

......


Subtraction rule


N B O NB BO NO NBO35 −25 −15 −12 +10 +7 +9 −5 4

Alfred N,O * * * *Bobby B

* *Cathy B,O * * * *Dave N,B,O * * * * * * * *Eddy - *

......


Subtraction rule


N B O NB BO NO NBO35 −25 −15 −12 +10 +7 +9 −5 4

Alfred N,O * * * *Bobby B * *Cathy B,O

* * * *Dave N,B,O * * * * * * * *Eddy - *

......


Subtraction rule


N B O NB BO NO NBO35 −25 −15 −12 +10 +7 +9 −5 4

Alfred N,O * * * *Bobby B * *Cathy B,O * * * *Dave N,B,O

* * * * * * * *Eddy - *

......


Subtraction rule


N B O NB BO NO NBO35 −25 −15 −12 +10 +7 +9 −5 4

Alfred N,O * * * *Bobby B * *Cathy B,O * * * *Dave N,B,O * * * * * * * *Eddy -

*...

...


Subtraction rule


N B O NB BO NO NBO35 −25 −15 −12 +10 +7 +9 −5 4

Alfred N,O * * * *Bobby B * *Cathy B,O * * * *Dave N,B,O * * * * * * * *Eddy - *

......


Subtraction rule


N B O NB BO NO NBO35 −25 −15 −12 +10 +7 +9 −5 4

Alfred N,O 1 -1 -1 +1 0Bobby B 1 -1 0Cathy B,O 1 -1 -1 +1 0Dave N,B,O 1 -1 -1 -1 +1 +1 +1 -1 0Eddy - 1 1

......


Subtraction rule

Let’s see how each one is counted

Alfred (N,O):

1−(

2

1

)+

(2

2

)= 1− 2 + 1 = 0

Bobby (B):

1−(

1

1

)= 1− 1 = 0

Dave (N,B,O):

1−(

3

1

)+

(3

2

)−(

3

3

)= 1− 3 + 3− 1 = 0

Do you see any patterns here? How about

1−(

5

1

)+

(5

2

)−(

5

3

)+

(5

4

)−(

5

5

)?


Subtraction rule


Alfred (N,O):

1−(

2

1

)+

(2

2

)=

1− 2 + 1 = 0

Bobby (B):

1−(

1

1

)= 1− 1 = 0

Dave (N,B,O):

1−(

3

1

)+

(3

2

)−(

3

3

)= 1− 3 + 3− 1 = 0


1−(

5

1

)+

(5

2

)−(

5

3

)+

(5

4

)−(

5

5

)?


Subtraction rule


Alfred (N,O):

1−(

2

1

)+

(2

2

)= 1− 2 + 1 = 0

Bobby (B):

1−(

1

1

)= 1− 1 = 0

Dave (N,B,O):

1−(

3

1

)+

(3

2

)−(

3

3

)= 1− 3 + 3− 1 = 0


1−(

5

1

)+

(5

2

)−(

5

3

)+

(5

4

)−(

5

5

)?


Subtraction rule


Alfred (N,O):

1−(

2

1

)+

(2

2

)= 1− 2 + 1 = 0

Bobby (B):

1−(

1

1

)=

1− 1 = 0

Dave (N,B,O):

1−(

3

1

)+

(3

2

)−(

3

3

)= 1− 3 + 3− 1 = 0


1−(

5

1

)+

(5

2

)−(

5

3

)+

(5

4

)−(

5

5

)?


Subtraction rule


Alfred (N,O):

1−(

2

1

)+

(2

2

)= 1− 2 + 1 = 0

Bobby (B):

1−(

1

1

)= 1− 1 = 0

Dave (N,B,O):

1−(

3

1

)+

(3

2

)−(

3

3

)= 1− 3 + 3− 1 = 0


1−(

5

1

)+

(5

2

)−(

5

3

)+

(5

4

)−(

5

5

)?


Subtraction rule


Alfred (N,O):

1−(

2

1

)+

(2

2

)= 1− 2 + 1 = 0

Bobby (B):

1−(

1

1

)= 1− 1 = 0

Dave (N,B,O):

1−(

3

1

)+

(3

2

)−(

3

3

)=

1− 3 + 3− 1 = 0


1−(

5

1

)+

(5

2

)−(

5

3

)+

(5

4

)−(

5

5

)?


Subtraction rule


Alfred (N,O):

1−(

2

1

)+

(2

2

)= 1− 2 + 1 = 0

Bobby (B):

1−(

1

1

)= 1− 1 = 0

Dave (N,B,O):

1−(

3

1

)+

(3

2

)−(

3

3

)= 1− 3 + 3− 1 = 0


1−(

5

1

)+

(5

2

)−(

5

3

)+

(5

4

)−(

5

5

)?


Subtraction rule


Alfred (N,O):

1−(

2

1

)+

(2

2

)= 1− 2 + 1 = 0

Bobby (B):

1−(

1

1

)= 1− 1 = 0

Dave (N,B,O):

1−(

3

1

)+

(3

2

)−(

3

3

)= 1− 3 + 3− 1 = 0

Do you see any patterns here?

How about

1−(

5

1

)+

(5

2

)−(

5

3

)+

(5

4

)−(

5

5

)?


Subtraction rule


Alfred (N,O):

1−(

2

1

)+

(2

2

)= 1− 2 + 1 = 0

Bobby (B):

1−(

1

1

)= 1− 1 = 0

Dave (N,B,O):

1−(

3

1

)+

(3

2

)−(

3

3

)= 1− 3 + 3− 1 = 0


1−(

5

1

)+

(5

2

)−(

5

3

)+

(5

4

)−(

5

5

)?


Subtraction rule

Underlying structures

Let’s write 1 as(50

). Also, let’s separate plus terms and minus terms:(

5

0

)+

(5

2

)+

(5

4

)♥

(5

1

)+

(5

3

)+

(5

5

)

Note that the left terms are the number of even subsets and the rightterms are the number of odd subsets.

Theorem: The number of even subsets is equal to the number ofodd subsets.


Subtraction rule




5

0

)+

(5

2

)+

(5

4

)♥

(5

1

)+

(5

3

)+

(5

5

)Note that the left terms are the number of even subsets and the rightterms are the number of odd subsets.



Subtraction rule




5

0

)+

(5

2

)+

(5

4

)♥

(5

1

)+

(5

3

)+

(5

5

)Note that the left terms are the number of even subsets and the rightterms are the number of odd subsets.



Subtraction rule

Example (1)

Question: How many positive integers not exceeding 1000 are divis-ible by 7 or 11?Solution: Let A and B be the sets of positive integers not exceeding1000 that are divisible by 7 and 11, respectively.

|A ∪ B| = |A|+ |B| − |A ∩ B| (1)

= b1000

7c+ b1000

11c − b 1000

7× 11c (2)

= 142 + 90− 12 = 220. (3)


Subtraction rule

# Onto functions

Question: How many onto functions are there from a set with sixelements to a set with three elements?

Solution: Let A = {a1, · · · , a6} and B = {b1, b2, b3}. Let Pi be theproperty that bi not in the range of the function.

|P1 ∪ P2 ∪ P3| = N − [|P1|+ |P2|+ |P3|]+ [|P1 ∩ P2|+ |P2 ∩ P3|+ |P1 ∩ P3|]− |P1 ∩ P2 ∩ P3|= 36 − C (3, 1)26 + C (3, 2)16 = 729− 192 + 3 = 540.

Theorem: Let m, n ∈ Z+ m ≥ n. Then, there are

n−1∑k=0

(−1)kC(n, k)(n−k)m = nm−C(n, 1)(n−1)m+· · ·+(−1)n−1C(n, n−1)1m

onto functions from a set with m elements to a set with n elements.


Subtraction rule

# Onto functions

Question: How many onto functions are there from a set with sixelements to a set with three elements?Solution: Let A = {a1, · · · , a6} and B = {b1, b2, b3}. Let Pi be theproperty that bi not in the range of the function.



n−1∑k=0




Subtraction rule

# Onto functions




n−1∑k=0




Subtraction rule

# Onto functions




n−1∑k=0




Subtraction rule

Derangement

Definition: A derangement is a permutation of objects that leavesno object in its original position.

Example

The permutation 21453 is a derangement of 12345 because nonumber is left in its original position. How about 21543?

Question: A new employee checks the hats of n people ata restaurant, forgetting to put claim check numbers on thehats. When customers return for their hats, the checker givesthem back hats chosen at random from the remaining hats.How many cases does no one receive the correct hat?


Subtraction rule

Derangement


Example

The permutation 21453 is a derangement of 12345 because nonumber is left in its original position.

How about 21543?



Subtraction rule

Derangement


Example




Subtraction rule

Derangement


Example




Subtraction rule

Theorem of derangement

Theorem: The number of derangements of a set with n elements is

Dn = n![1− 1

1!+

1

2!− 1

3!+ · · ·+ (−1)n

1

n!].

Proof: Let a permutation have property Pi if it fixes element i . Thenumber of derangements is the number of permutations having noneof the properties Pi for i = 1, 2, · · · , n.

Dn = |P1 ∪ P2 ∪ P3 ∪ · · · ∪ Pn| = N −∑i

|Pi |

+∑i<j

|Pi ∩ Pj | −∑

i<j<k

|Pi ∩ Pj ∩ Pk |+ · · ·+ (−1)n|P1 ∩ · · · ∩ Pn|

= n! +n∑

k=1

(−1)kC (n, k)(n − k)! = n! +n∑

k=1

(−1)kn!

k!(n − k)!(n − k)!


Subtraction rule



Dn = n![1− 1

1!+

1

2!− 1

3!+ · · ·+ (−1)n

1

n!].


Dn = |P1 ∪ P2 ∪ P3 ∪ · · · ∪ Pn| = N −∑i

|Pi |

+∑i<j

|Pi ∩ Pj | −∑

i<j<k

|Pi ∩ Pj ∩ Pk |+ · · ·+ (−1)n|P1 ∩ · · · ∩ Pn|

= n! +n∑

k=1

(−1)kC (n, k)(n − k)! = n! +n∑

k=1

(−1)kn!

k!(n − k)!(n − k)!


Subtraction rule



Dn = n![1− 1

1!+

1

2!− 1

3!+ · · ·+ (−1)n

1

n!].


Dn = |P1 ∪ P2 ∪ P3 ∪ · · · ∪ Pn| = N −∑i

|Pi |

+∑i<j

|Pi ∩ Pj | −∑

i<j<k

|Pi ∩ Pj ∩ Pk |+ · · ·+ (−1)n|P1 ∩ · · · ∩ Pn|

= n! +n∑

k=1

(−1)kC (n, k)(n − k)! = n! +n∑

k=1

(−1)kn!

k!(n − k)!(n − k)!


Subtraction rule

Example

Question: A new employee checks the hats of 5 people at a restau-rant, forgetting to put claim check numbers on the hats. Whencustomers return for their hats, the checker gives them back hatschosen at random from the remaining hats. How many cases doesat least one receive the correct hat?

Solution: Let Di denote the number of derangements on i elements.The number is

Task NumberWay 1: derangement of 4 hats C (5, 1)D4 45Way 2: derangement of 3 hats C (5, 2)D3 20Way 3: derangement of 2 hats C (5, 3)D2 10Way 4: derangement of 1 hats C (5, 4)D1 0Way 5: derangement of 0 hats C (5, 5)D0 1

Therefore, the total number of cases is 76. (Note that the case ofD1 is impossible, i.e,. D1 = 0.)


Subtraction rule

Example

Question: A new employee checks the hats of 5 people at a restau-rant, forgetting to put claim check numbers on the hats. Whencustomers return for their hats, the checker gives them back hatschosen at random from the remaining hats. How many cases doesat least one receive the correct hat?Solution: Let Di denote the number of derangements on i elements.The number is




Subtraction rule

Example


Task Number

Way 1: derangement of 4 hats C (5, 1)D4 45Way 2: derangement of 3 hats C (5, 2)D3 20Way 3: derangement of 2 hats C (5, 3)D2 10Way 4: derangement of 1 hats C (5, 4)D1 0Way 5: derangement of 0 hats C (5, 5)D0 1



Subtraction rule

Example





Subtraction rule

Example





Subtraction rule Permutations with Indistinguishable Objects

Easy anagrams

An anagram of a particular word is a word that uses the same set ofalphabets. For example, the anagrams of ADD are ADD, DAD, andDDA.

How many anagrams does “ABCD” have?

4!, because every permutation of A B C or D is a different anagram.



Easy anagrams






Easy anagrams






Easy anagrams






Harder anagrams

How many anagrams does “ABCC ” have? Is it 4! ?

This time we have to be careful because the answer of 4! is too largeas it over counts many anagrams, i.e., it “distinguishes” the two C ’s.Let’s try to be concrete. How many times does “CABC ” get countedin 4!?If we treat two C ’s differently as C1 and C2, we can see that CABC iscounted twice as C1ABC2 and C2ABC1. This is true for any anagramof ABCC .Since each anagram is counted in 4! twice, the number of anagrams is4!/2 = 4 · 3 = 12.



Harder anagrams


This time we have to be careful because the answer of 4! is too largeas it over counts many anagrams, i.e., it “distinguishes” the two C ’s.

Let’s try to be concrete. How many times does “CABC ” get countedin 4!?If we treat two C ’s differently as C1 and C2, we can see that CABC iscounted twice as C1ABC2 and C2ABC1. This is true for any anagramof ABCC .Since each anagram is counted in 4! twice, the number of anagrams is4!/2 = 4 · 3 = 12.



Harder anagrams


This time we have to be careful because the answer of 4! is too largeas it over counts many anagrams, i.e., it “distinguishes” the two C ’s.Let’s try to be concrete. How many times does “CABC ” get countedin 4!?

If we treat two C ’s differently as C1 and C2, we can see that CABC iscounted twice as C1ABC2 and C2ABC1. This is true for any anagramof ABCC .Since each anagram is counted in 4! twice, the number of anagrams is4!/2 = 4 · 3 = 12.



Harder anagrams


This time we have to be careful because the answer of 4! is too largeas it over counts many anagrams, i.e., it “distinguishes” the two C ’s.Let’s try to be concrete. How many times does “CABC ” get countedin 4!?If we treat two C ’s differently as C1 and C2, we can see that CABC iscounted twice as C1ABC2 and C2ABC1. This is true for any anagramof ABCC .

Since each anagram is counted in 4! twice, the number of anagrams is4!/2 = 4 · 3 = 12.



Harder anagrams


This time we have to be careful because the answer of 4! is too largeas it over counts many anagrams, i.e., it “distinguishes” the two C ’s.Let’s try to be concrete. How many times does “CABC ” get countedin 4!?If we treat two C ’s differently as C1 and C2, we can see that CABC iscounted twice as C1ABC2 and C2ABC1. This is true for any anagramof ABCC .Since each anagram is counted in 4! twice, the number of anagrams is4!/2 = 4 · 3 = 12.



General anagrams

Let’s try to use the same approach to count the anagram ofHELLOWORLD. (It has 3 L’s, 2 O’s, H, E , W , R, and D.)

The number of permutation of alphabets in HELLOWORLD, treating eachcharacter differently is 10!. However, each anagram is counted for 3!2!times because of the 3 copies of L and the 2 copies of O. Therefore, thenumber of anagrams is

10!

3!2!.



General anagrams

Let’s try to use the same approach to count the anagram ofHELLOWORLD. (It has 3 L’s, 2 O’s, H, E , W , R, and D.)

The number of permutation of alphabets in HELLOWORLD, treating eachcharacter differently is 10!. However, each anagram is counted for 3!2!times because of the 3 copies of L and the 2 copies of O. Therefore, thenumber of anagrams is

10!

3!2!.



Generalization

The number of different permutations of n objects, where there aren1 indistinguishable objects of type 1, n2 indistinguishable objects oftype 2,· · · , and nk indistinguishable objects of type k , is

n!

n1!n2! · · · nk !.


Distributing Objects into Boxes Distinguishable Objects and Distinguishable Boxes

Distributing presents

I have 9 different presents. I want to give them to 3 students: A, B,and C. I want to give each student 3 presents. In how many wayscan I do it?

Let’s think about the process of distributing the presents. We can first let Achoose 3 presents, then B chooses the next 3 presents, and C chooses thelast 3 presents. If we distinguish the order which each child chooses thepresents, then there are 9! ways. However, in this case, we consider thedistribution of presents, i.e., we consider the set of presents each child gets.

To see how many times each distribution is counted in the 9! ways, we canlet children form a line and let each child permute his or her presents. Eachchild has 3! choices. Thus, one distribution appears 3!3!3! times.

Thus, the number of ways we can distribute presents is

9!

3!3!3!





Let’s think about the process of distributing the presents.

We can first let Achoose 3 presents, then B chooses the next 3 presents, and C chooses thelast 3 presents. If we distinguish the order which each child chooses thepresents, then there are 9! ways. However, in this case, we consider thedistribution of presents, i.e., we consider the set of presents each child gets.



9!

3!3!3!





Let’s think about the process of distributing the presents. We can first let Achoose 3 presents, then B chooses the next 3 presents, and C chooses thelast 3 presents.

If we distinguish the order which each child chooses thepresents, then there are 9! ways. However, in this case, we consider thedistribution of presents, i.e., we consider the set of presents each child gets.



9!

3!3!3!





Let’s think about the process of distributing the presents. We can first let Achoose 3 presents, then B chooses the next 3 presents, and C chooses thelast 3 presents. If we distinguish the order which each child chooses thepresents, then there are 9! ways.

However, in this case, we consider thedistribution of presents, i.e., we consider the set of presents each child gets.



9!

3!3!3!








9!

3!3!3!








9!

3!3!3!








9!

3!3!3!



Another way to look at the present distribution

Let’s look closely at a particular present distribution in the previousquestion. Let {1, 2, . . . , 9} be the set of presents.

Consider the case where A gets {1, 3, 8}, B gets {2, 4, 6}, and C gets{5, 7, 9}.

Another way to look at this distribution is to fix the order of thepresents and see who gets each of the presents. Thus, the previousdistribution is represented in the following table:

Presents 1 2 3 4 5 6 7 8 9

Children A B A B C B C A C

This is essentially an anagram problem. You can think of oneparticular way of present distribution as anagram of AAABBBCCC.Thus, we reach the same solution of

9!

3!3!3!.





Consider the case where A gets {1, 3, 8}, B gets {2, 4, 6}, and C gets{5, 7, 9}.Another way to look at this distribution is to fix the order of thepresents and see who gets each of the presents. Thus, the previousdistribution is represented in the following table:

Presents 1 2 3 4 5 6 7 8 9



9!

3!3!3!.





Consider the case where A gets {1, 3, 8}, B gets {2, 4, 6}, and C gets{5, 7, 9}.Another way to look at this distribution is to fix the order of thepresents and see who gets each of the presents. Thus, the previousdistribution is represented in the following table:

Presents 1 2 3 4 5 6 7 8 9



9!

3!3!3!.



Generalization

The number of ways to distribute n distinguishable objects into kdistinguishable boxes so that ni objects are placed into box i , i =1, 2, · · · , k, equals

n!

n1!n2! · · · nk !.


Distributing Objects into Boxes Indistinguishable Objects and Distinguishable Boxes

Indistinguishable objects and distinguishable boxes

How many ways are there to place 10 indistinguishable balls intoeight distinguishable bins?Solution: The number of ways to place 10 indistinguishable ballsinto eight bins equals the number of 10-combinations from a setwith eight elements when repetition is allowed. Consequently, thereare

C (8 + 10− 1, 10) = C (17, 10).

Remark: This means that there are C (n + r − 1, n − 1) ways to place rindistinguishable objects into n distinguishable boxes.

Distributing coins

I have 9 indentical coins. I want to give them to 3 students: A, B,and C. In how many ways can I do it, given that some student maynot get any coins?



Indistinguishable objects and distinguishable boxes

How many ways are there to place 10 indistinguishable balls intoeight distinguishable bins?Solution: The number of ways to place 10 indistinguishable ballsinto eight bins equals the number of 10-combinations from a setwith eight elements when repetition is allowed. Consequently, thereare

C (8 + 10− 1, 10) = C (17, 10).

Remark: This means that there are C (n + r − 1, n − 1) ways to place rindistinguishable objects into n distinguishable boxes.

Distributing coins

I have 9 indentical coins. I want to give them to 3 students: A, B,and C. In how many ways can I do it, given that some student maynot get any coins?



Distributing coins (1)

I have 9 indentical coins. I want to give them to 3 students: A, B,and C. In how many ways can I do it so that each student gets atleast one coin?

Let’s first try to organize the distribution of coins.

We place all 9coins in a line. We let the first student picks some coin, then thesecond student, then the last one.

Since each coin is identical, we can let the first student picks the coinfrom the beginning of the line. Then the second one pick the next setof coins, and so on.

One possible distribution is

oo︸︷︷︸1

oooo︸︷︷︸2

ooo︸︷︷︸3

In how many ways can we do that?





Let’s first try to organize the distribution of coins. We place all 9coins in a line. We let the first student picks some coin, then thesecond student, then the last one.



oo︸︷︷︸1

oooo︸︷︷︸2

ooo︸︷︷︸3









oo︸︷︷︸1

oooo︸︷︷︸2

ooo︸︷︷︸3









oo︸︷︷︸1

oooo︸︷︷︸2

ooo︸︷︷︸3









oo︸︷︷︸1

oooo︸︷︷︸2

ooo︸︷︷︸3





The example below provides us with a hint on how to count.

oo︸︷︷︸1

oooo︸︷︷︸2

ooo︸︷︷︸3

Since all coins are identical, what matters are where the first student andthe second student stop picking the coins. I.e, the previous example canbe depicted as

oo|oooo|ooo

Thus, in how many ways can we do that?Since there are 8 places we can mark starting points, and there are 2starting points we have to place, then there are

(82

)ways to do so.

This is a fairly surprising use of binomial coefficients.





oo︸︷︷︸1

oooo︸︷︷︸2

ooo︸︷︷︸3

Since all coins are identical, what matters are where the first student andthe second student stop picking the coins.

I.e, the previous example canbe depicted as

oo|oooo|ooo


(82

)ways to do so.






oo︸︷︷︸1

oooo︸︷︷︸2

ooo︸︷︷︸3


oo|oooo|ooo

Thus, in how many ways can we do that?

Since there are 8 places we can mark starting points, and there are 2starting points we have to place, then there are

(82

)ways to do so.






oo︸︷︷︸1

oooo︸︷︷︸2

ooo︸︷︷︸3


oo|oooo|ooo


(82

)ways to do so.






oo︸︷︷︸1

oooo︸︷︷︸2

ooo︸︷︷︸3


oo|oooo|ooo


(82

)ways to do so.





Let’s consider a general problem where we have n identical coins to giveout to k students so that each student gets at least one coin. In howmany ways can we do that?

Since there are n − 1 places between n coins and we need to place k − 1starting points, there are

(n−1k−1)

ways to do so.

There are(n−1k−1)

ways to distribute n identical coins to k children sothat each child get at least one coin.




Let’s consider a general problem where we have n identical coins to giveout to k students so that each student gets at least one coin. In howmany ways can we do that?Since there are n − 1 places between n coins and we need to place k − 1starting points, there are

(n−1k−1)

ways to do so.






Let’s consider a general problem where we have n identical coins to giveout to k students so that each student gets at least one coin. In howmany ways can we do that?Since there are n − 1 places between n coins and we need to place k − 1starting points, there are

(n−1k−1)

ways to do so.




Distributing Objects into Boxes Distinguishable Objects and Indistinguishable Boxes

Distinguishable objects and indistinguishable boxes

How many ways are there to put four different employees into threeindistinguishable offices, when each office can contain any numberof employees?

Solution:Way CountingWay 1: oooo C (4, 4)Way 2: ooo|o C (4, 3)Way 3: oo|oo C (4, 2)/P(2, 2)Way 4: oo|o|o C (4, 2)/P(2, 2)

Therefore, we find that there are 14 ways to put four different em-ployees into three indistinguishable offices.




How many ways are there to put four different employees into threeindistinguishable offices, when each office can contain any numberof employees?Solution:

Way Counting

Way 1: oooo C (4, 4)Way 2: ooo|o C (4, 3)Way 3: oo|oo C (4, 2)/P(2, 2)Way 4: oo|o|o C (4, 2)/P(2, 2)






Way CountingWay 1: oooo C (4, 4)Way 2: ooo|o C (4, 3)Way 3: oo|oo C (4, 2)/P(2, 2)Way 4: oo|o|o C (4, 2)/P(2, 2)






Way CountingWay 1: oooo C (4, 4)Way 2: ooo|o C (4, 3)Way 3: oo|oo C (4, 2)/P(2, 2)Way 4: oo|o|o C (4, 2)/P(2, 2)




Stirling numbers of the second kind

Question: How many ways are there to distribute n distinguishableobjects into m indistinguishable boxes?

Solution:

Let S(n, j) be # ways to distribute n distinguishable objectsinto j indistinguishable boxes s.t. no box is empty, whereS(n, j) denotes the Stirling numbers of the second kind.

Considering boxes are distinguishable;

It truly counts # onto functions;There are

∑j−1k=0(−1)kC (j , k)(j − k)n onto functions from a set

with m elements to a set with n elements.

Hence, S(n, j) = 1j!

∑j−1k=0(−1)kC (j , k)(j − k)n.

Therefore, there are∑m

j=1 S(n, j) ways to distribute n distinguishableobjects into m indistinguishable boxes.




Question: How many ways are there to distribute n distinguishableobjects into m indistinguishable boxes?Solution:







∑j−1k=0(−1)kC (j , k)(j − k)n.













∑j−1k=0(−1)kC (j , k)(j − k)n.













∑j−1k=0(−1)kC (j , k)(j − k)n.













∑j−1k=0(−1)kC (j , k)(j − k)n.













∑j−1k=0(−1)kC (j , k)(j − k)n.




Distributing Objects into Boxes Indistinguishable Objects and Indistinguishable Boxes

Indistinguishable objects and indistinguishable boxes

How many ways are there to pack six copies of the same book intofour identical boxes, where a box can contain as many as six books?

Solution:Way CountingWay 1: oooooo 1Way 2: ooooo|o 1Way 3: oooo|oo 1Way 4: oooo|o|o 1Way 5: ooo|ooo 1Way 6: ooo|oo|o 1Way 7: ooo|o|o|o 1Way 8: oo|oo|oo 1Way 9: oo|oo|o|o 1

We conclude that there are nine allowable ways to pack the books,because we have listed them all.




How many ways are there to pack six copies of the same book intofour identical boxes, where a box can contain as many as six books?Solution:

Way Counting

Way 1: oooooo 1Way 2: ooooo|o 1Way 3: oooo|oo 1Way 4: oooo|o|o 1Way 5: ooo|ooo 1Way 6: ooo|oo|o 1Way 7: ooo|o|o|o 1Way 8: oo|oo|oo 1Way 9: oo|oo|o|o 1






Way CountingWay 1: oooooo 1Way 2: ooooo|o 1Way 3: oooo|oo 1Way 4: oooo|o|o 1Way 5: ooo|ooo 1Way 6: ooo|oo|o 1Way 7: ooo|o|o|o 1Way 8: oo|oo|oo 1Way 9: oo|oo|o|o 1






Way CountingWay 1: oooooo 1Way 2: ooooo|o 1Way 3: oooo|oo 1Way 4: oooo|o|o 1Way 5: ooo|ooo 1Way 6: ooo|oo|o 1Way 7: ooo|o|o|o 1Way 8: oo|oo|oo 1Way 9: oo|oo|o|o 1




Example


Question: How many permutations of number 1, 2, 3, 4, 5, 6, 7,and 8 contain

number string 234?

number strings 23 and 45?


Solution:

P(6, 6);

P(6, 6);

P(4, 4).



Example


Question: How many permutations of number 1, 2, 3, 4, 5, 6, 7,and 8 contain

number string 234?



Solution:

P(6, 6);

P(6, 6);

P(4, 4).



Example

The problem of grouping

Question: How many cases for grouping eight books into groups?

each group has four books?

each group has two books?

the numbers of books in the four groups are 1, 2, 2, 3?

three persons take 2, 2, and 4 books?

Solution:C(8,4)C(4,4)

P(2,2) ;

C(8,2)C(6,2)C(4,2)C(2,2)P(4,4) ;

C(8,1)C(7,2)C(5,2)C(3,3)P(2,2) ;

C(8,2)C(6,2)C(4,4)P(2,2) · P(3, 3);



Example

The problem of grouping

Question: How many cases for grouping eight books into groups?

each group has four books?

each group has two books?

the numbers of books in the four groups are 1, 2, 2, 3?

three persons take 2, 2, and 4 books?

Solution:C(8,4)C(4,4)

P(2,2) ;

C(8,2)C(6,2)C(4,2)C(2,2)P(4,4) ;

C(8,1)C(7,2)C(5,2)C(3,3)P(2,2) ;

C(8,2)C(6,2)C(4,4)P(2,2) · P(3, 3);


Generating Permutations and Combinations

Generating permutations

Example: Permutation 23415 of set {1, 2, 3, 4, 5} precedes the per-mutation 23514. Similarly, permutation 41532 precedes 52143.Question: What is the next permutation in lexicographic order after32541?

Demonstration

Step Result32541 3254132541 3254132541 3452134521 34125





Demonstration

Step Result

32541 3254132541 3254132541 3452134521 34125





Demonstration

Step Result32541 3254132541 3254132541 3452134521 34125



Generating the next larger bit string

Question: Find the next bit string after 10 0010 0111.

Algorithm:

Demonstration:Step Result1000100111 10001001101000100110 10001001001000100100 10001000001000100000 1000101000




Question: Find the next bit string after 10 0010 0111.Algorithm:

Demonstration:Step Result

1000100111 10001001101000100110 10001001001000100100 10001000001000100000 1000101000




Question: Find the next bit string after 10 0010 0111.Algorithm:

Demonstration:Step Result1000100111 10001001101000100110 10001001001000100100 10001000001000100000 1000101000



Generating the next r-combination in lexicographic order.

Question: Find the next larger 4-combination of the set{1, 2, 3, 4, 5, 6} after {1, 2, 5, 6}.

Algorithm:

Demonstration: (where r = 4 and n = 6)Step Result{1, 2, 5, 6} {1, 3, 5, 6}{1, 3, 5, 6} {1, 3, 4, 6}{1, 3, 4, 6} {1, 3, 4, 5}




Question: Find the next larger 4-combination of the set{1, 2, 3, 4, 5, 6} after {1, 2, 5, 6}.Algorithm:

Demonstration: (where r = 4 and n = 6)Step Result

{1, 2, 5, 6} {1, 3, 5, 6}{1, 3, 5, 6} {1, 3, 4, 6}{1, 3, 4, 6} {1, 3, 4, 5}




Question: Find the next larger 4-combination of the set{1, 2, 3, 4, 5, 6} after {1, 2, 5, 6}.Algorithm:

Demonstration: (where r = 4 and n = 6)Step Result{1, 2, 5, 6} {1, 3, 5, 6}{1, 3, 5, 6} {1, 3, 4, 6}{1, 3, 4, 6} {1, 3, 4, 5}


Take-aways

Take-aways

Conclusions

Counting principles

Product ruleSum ruleSubtraction ruleDivision rule

Permutations

Combinations


Documents

Discrete Mathematics and Its Applicationsdase.ecnu.edu.cn/mgao/teaching/DM_2020_Spring/slides/3_counting… · Indistinguishable Objects and Indistinguishable Boxes 7 Generating Permutations