One, two, three, we’re…
Counting
1
Basic Counting Principles
Counting problems are of the following kind:
“How many different 8-letter passwords are
there?”
“How many possible ways are there to pick
11 soccer players out of a 20-player team?”
Most importantly, counting is the basis for
computing probabilities of discrete events.
(“What is the probability of winning the
lottery?”)
2
The sum rule:
If a task can be done in n1 ways and a second task in n2
ways, and if these two tasks cannot be done at the same
time, then there are n1 + n2 ways to do either task.
Example:
The department will award a free computer to either a CS
student or a CS professor.
How many different choices are there, if there are 530
students and 15 professors?
There are 530 + 15 = 545 choices.
3
Basic Counting Principles
Generalized sum rule:
 If we have tasks T1, T2, …, Tm that can be
done in n1, n2, …, nm ways, respectively, and
no two of these tasks can be done at the
same time, then there are n1 + n2 + … + nm
ways to do one of these tasks.
4
Basic Counting Principles
The product rule:
Suppose that a procedure can be broken
down into two successive tasks. If there are n1
ways to do the first task and n2 ways to do the
second task after the first task has been done,
then there are n1n2 ways to do the procedure.
5
Basic Counting Principles
Example:
How many different license plates are there that containing
exactly three English letters ?
Solution:
There are 26 possibilities to pick the first letter, then 26
possibilities for the second one, and 26 for the last one.
So there are 262626 = 17576 different license plates.
6
Basic Counting Principles
Generalized product rule:
If we have a procedure consisting of
sequential tasks T1, T2, …, Tm that can be
done in n1, n2, …, nm ways, respectively, then
there are n1  n2  …  nm ways to carry
out the procedure.
7
Basic Counting Principles
The sum and product rules can also be phrased in
terms of set theory.
Sum rule: Let A1, A2, …, Am be disjoint sets. Then the
number of ways to choose any element from one of
these sets is |A1  A2  …  Am | =
|A1| + |A2| + … + |Am|.
Product rule: Let A1, A2, …, Am be finite sets. Then the
number of ways to choose one element from each set
in the order A1, A2, …, Am is
|A1  A2  …  Am | = |A1|  |A2|  …  |Am|.
8
Basic Counting Principles
Inclusion-Exclusion
How many bit strings of length 8 either start with a 1 or
end with 00?
Task 1: Construct a string of length 8 that starts with a 1.
There is one way to pick the first bit (1),
two ways to pick the second bit (0 or 1),
two ways to pick the third bit (0 or 1),
.
.
.
two ways to pick the eighth bit (0 or 1).
Product rule: Task 1 can be done in 127
= 128 ways.
9
Task 2: Construct a string of length 8 that ends
with 00.
There are two ways to pick the first bit (0 or 1),
two ways to pick the second bit (0 or 1),
.
.
.
two ways to pick the sixth bit (0 or 1),
one way to pick the seventh bit (0), and
one way to pick the eighth bit (0).
Product rule: Task 2 can be done in 26
= 64 ways.
10
Inclusion-Exclusion
Since there are 128 ways to do Task 1 and 64 ways to do
Task 2, does this mean that there are 192 bit strings either
starting with 1 or ending with 00 ?
No, because here Task 1 and Task 2 can be done at the
same time.
When we carry out Task 1 and create strings starting with 1,
some of these strings end with 00.
Therefore, we sometimes do Tasks 1 and 2 at the same
time, so the sum rule does not apply.
11
Inclusion-Exclusion
If we want to use the sum rule in such a case, we
have to subtract the cases when Tasks 1 and 2 are
done at the same time.
How many cases are there, that is, how many
strings start with 1 and end with 00?
There is one way to pick the first bit (1),
two ways for the second, …, sixth bit (0 or 1),
one way for the seventh, eighth bit (0).
Product rule: In 25
= 32 cases, Tasks 1 and 2 are
carried out at the same time.
12
Inclusion-Exclusion
Since there are 128 ways to complete Task 1 and 64 ways
to complete Task 2, and in 32 of these cases Tasks 1 and 2
are completed at the same time, there are
128 + 64 – 32 = 160 ways to do either task.
In set theory, this corresponds to sets A1 and A2 that are
not disjoint. Then we have:
|A1  A2| = |A1| + |A2| - |A1  A2|
This is called the principle of inclusion-exclusion.
13
Inclusion-Exclusion
Tree Diagrams
How many bit strings of length four do not have two
consecutive 1s?
 Task 1 Task 2 Task 3 Task 4
(1st
bit) (2nd
bit) (3rd
bit) (4th
bit)
14
0
0
0
0
1
1
0
1 0 0
1
1 0
0 0
1
1
0
There are 8 strings.
The Pigeonhole Principle
The pigeonhole principle: If (k + 1) or more objects
are placed into k boxes, then there is at least one
box containing two or more of the objects.
Example 1: If there are 11 players in a soccer
team that wins 12-0, there must be at least one
player in the team who scored at least twice.
Example 2: If you have 6 classes from Monday to
Friday, there must be at least one day on which you
have at least two classes.
15
The generalized pigeonhole principle: If N
objects are placed into k boxes, then there is at
least one box containing at least N/k of the
objects.
Example 1: In our 60-student class, at least 12
students will get the same letter grade (A, B, C,
D, or F).
16
The Pigeonhole Principle
Example 2: Assume you have a drawer containing
a random distribution of a dozen brown socks and a
dozen black socks. It is dark, so how many socks do
you have to pick to be sure that among them there
is a matching pair?
There are two types of socks, so if you pick at least
3 socks, there must be either at least two brown
socks or at least two black socks.
Generalized pigeonhole principle: 3/2 = 2.
17
The Pigeonhole Principle
Permutations and Combinations
How many ways are there to pick a set of 3 people from a
group of 6?
There are 6 choices for the first person, 5 for the second
one, and 4 for the third one, so there are
654 = 120 ways to do this.
This is not the correct result!
For example, picking person C, then person A, and then
person E leads to the same group as first picking E, then C,
and then A.
However, these cases are counted separately in the
above equation.
18
So how can we compute how many different subsets of
people can be picked (that is, we want to disregard the
order of picking) ?
To find out about this, we need to look at permutations.
A permutation of a set of distinct objects is an ordered
arrangement of these objects.
An ordered arrangement of r elements of a set is called an
r-permutation.
19
Permutations and Combinations
Example: Let S = {1, 2, 3}.
The arrangement 3, 1, 2 is a permutation of S.
The arrangement 3, 2 is a 2-permutation of S.
The number of r-permutations of a set with n distinct
elements is denoted by P(n, r).
We can calculate P(n, r) with the product rule:
P(n, r) = n(n – 1)(n – 2) …(n – r + 1).
(n choices for the first element, (n – 1) for the second one,
(n – 2) for the third one…)
20
Permutations and Combinations
Example:
P(8, 3) = 876 = 336
 = (87654321)/(54321)
General formula:
P(n, r) = n!/(n – r)!
Knowing this, we can return to our initial question:
How many ways are there to pick a set of 3 people from a
group of 6 (disregarding the order of picking)?
21
Permutations and Combinations
An r-combination of elements of a set is an unordered
selection of r elements from the set.
Thus, an r-combination is simply a subset of the set with r
elements.
Example: Let S = {1, 2, 3, 4}.
Then {1, 3, 4} is a 3-combination from S.
The number of r-combinations of a set with n distinct
elements is denoted by C(n, r).
Example: C(4, 2) = 6, since, for example, the 2-
combinations of a set {1, 2, 3, 4} are {1, 2}, {1, 3}, {1, 4}, {2, 3},
{2, 4}, {3, 4}.
22
Permutations and Combinations
How can we calculate C(n, r)?
Consider that we can obtain the r-permutation of a set in
the following way:
First, we form all the r-combinations of the set
(there are C(n, r) such r-combinations).
Then, we generate all possible orderings in each of these r-
combinations (there are P(r, r) such orderings in each case).
Therefore, we have:
P(n, r) = C(n, r)P(r, r)
23
Permutations and Combinations
C(n, r) = P(n, r)/P(r, r)
 = n!/(n – r)!/(r!/(r – r)!)
 = n!/(r!(n – r)!)
Now we can answer our initial question:
How many ways are there to pick a set of 3 people from a
group of 6 (disregarding the order of picking)?
C(6, 3) = 6!/(3!3!) = 720/(66) = 720/36 = 20
There are 20 different ways, that is, 20 different groups to be
picked.
24
Permutations and Combinations
Corollary:
Let n and r be nonnegative integers with r  n.
Then C(n, r) = C(n, n – r).
Note that “picking a group of r people from a
group of n people” is the same as “splitting a group
of n people into a group of r people and another
group of (n – r) people”.
Please also look at proof on page 252.
25
Permutations and Combinations
Example:
A soccer club has 8 female and 7 male
members. For today’s match, the coach wants
to have 6 female and 5 male players on the
grass. How many possible configurations are
there?
C(8, 6)  C(7, 5) = 8!/(6!2!)  7!/(5!2!)
 = 2821
 = 588
26
Permutations and Combinations
Combinations 27
)
,
(
!
)!
(
!
)]!
(
[
)!
(
!
)
,
( r
n
C
r
r
n
n
r
n
n
r
n
n
r
n
n
C 







This symmetry is intuitively plausible. For example, let
us consider a set containing six elements (n = 6).
Picking two elements and leaving four is essentially
the same as picking four elements and leaving two.
In either case, our number of choices is the number
of possibilities to divide the set into one set
containing two elements and another set containing
four elements.
Pascal’s Identity:
Let n and k be positive integers with n  k.
Then C(n + 1, k) = C(n, k – 1) + C(n, k).
How can this be explained?
What is it good for?
28
Combinations
Imagine a set S containing n elements and a set T containing
(n + 1) elements, namely all elements in S plus a new element
a.
Calculating C(n + 1, k) is equivalent to answering the
question: How many subsets of T containing k items are there?
Case I: The subset contains (k – 1) elements of S
plus the element a: C(n, k – 1) choices.
Case II: The subset contains k elements of S and
does not contain a: C(n, k) choices.
Sum Rule: C(n + 1, k) = C(n, k – 1) + C(n, k).
29
Combinations
Pascal’s Triangle
In Pascal’s triangle, each number is the sum of the
numbers to its upper left and upper right:
30
1
1 1
1 2 1
1 3 3 1
1 4 6 4 1
… … … … … …
Since we have C(n + 1, k) = C(n, k – 1) + C(n, k) and
C(0, 0) = 1, we can use Pascal’s triangle to simplify the
computation of C(n, k):
31
C(0, 0) = 1
C(1, 0) = 1 C(1, 1) = 1
C(2, 0) = 1 C(2, 1) = 2 C(2, 2) = 1
C(3, 0) = 1 C(3, 1) = 3 C(3, 2) = 3 C(3, 3) = 1
C(4, 0) = 1 C(4, 1) = 4 C(4, 2) = 6 C(4, 3) = 4 C(4, 4) = 1
k
n
Pascal’s Triangle
Binomial Coefficients
Expressions of the form C(n, k) are also called binomial
coefficients.
How come?
A binomial expression is the sum of two terms, such as (a + b).
Now consider (a + b)2
= (a + b)(a + b).
When expanding such expressions, we have to form all
possible products of a term in the first factor and a term in the
second factor:
(a + b)2
= a·a + a·b + b·a + b·b
Then we can sum identical terms:
(a + b)2
= a2
+ 2ab + b2
32
For (a + b)3
= (a + b)(a + b)(a + b) we have
(a + b)3
= aaa + aab + aba + abb + baa + bab + bba + bbb
(a + b)3
= a3
+ 3a2
b + 3ab2
+ b3
There is only one term a3
, because there is only one possibility
to form it: Choose a from all three factors: C(3, 3) = 1.
There is three times the term a2
b, because there are three
possibilities to choose a from two out of the three factors:
C(3, 2) = 3.
Similarly, there is three times the term ab2
(C(3, 1) = 3) and once the term b3
(C(3, 0) = 1).
33
Binomial Coefficients
This leads us to the following formula:
34
j
n
j
j
n
n
b
a
j
n
C
b
a 





0
)
,
(
)
(
With the help of Pascal’s triangle, this formula can
considerably simplify the process of expanding
powers of binomial expressions.
For example, the fifth row of Pascal’s triangle
(1 – 4 – 6 – 4 – 1) helps us to compute (a + b)4
:
(a + b)4
= a4
+ 4a3
b + 6a2
b2
+ 4ab3
+ b4
(Binomial Theorem)
Binomial Coefficients

COUNTING (permutation and combination).pptx

  • 1.
    One, two, three,we’re… Counting 1
  • 2.
    Basic Counting Principles Countingproblems are of the following kind: “How many different 8-letter passwords are there?” “How many possible ways are there to pick 11 soccer players out of a 20-player team?” Most importantly, counting is the basis for computing probabilities of discrete events. (“What is the probability of winning the lottery?”) 2
  • 3.
    The sum rule: Ifa task can be done in n1 ways and a second task in n2 ways, and if these two tasks cannot be done at the same time, then there are n1 + n2 ways to do either task. Example: The department will award a free computer to either a CS student or a CS professor. How many different choices are there, if there are 530 students and 15 professors? There are 530 + 15 = 545 choices. 3 Basic Counting Principles
  • 4.
    Generalized sum rule: If we have tasks T1, T2, …, Tm that can be done in n1, n2, …, nm ways, respectively, and no two of these tasks can be done at the same time, then there are n1 + n2 + … + nm ways to do one of these tasks. 4 Basic Counting Principles
  • 5.
    The product rule: Supposethat a procedure can be broken down into two successive tasks. If there are n1 ways to do the first task and n2 ways to do the second task after the first task has been done, then there are n1n2 ways to do the procedure. 5 Basic Counting Principles
  • 6.
    Example: How many differentlicense plates are there that containing exactly three English letters ? Solution: There are 26 possibilities to pick the first letter, then 26 possibilities for the second one, and 26 for the last one. So there are 262626 = 17576 different license plates. 6 Basic Counting Principles
  • 7.
    Generalized product rule: Ifwe have a procedure consisting of sequential tasks T1, T2, …, Tm that can be done in n1, n2, …, nm ways, respectively, then there are n1  n2  …  nm ways to carry out the procedure. 7 Basic Counting Principles
  • 8.
    The sum andproduct rules can also be phrased in terms of set theory. Sum rule: Let A1, A2, …, Am be disjoint sets. Then the number of ways to choose any element from one of these sets is |A1  A2  …  Am | = |A1| + |A2| + … + |Am|. Product rule: Let A1, A2, …, Am be finite sets. Then the number of ways to choose one element from each set in the order A1, A2, …, Am is |A1  A2  …  Am | = |A1|  |A2|  …  |Am|. 8 Basic Counting Principles
  • 9.
    Inclusion-Exclusion How many bitstrings of length 8 either start with a 1 or end with 00? Task 1: Construct a string of length 8 that starts with a 1. There is one way to pick the first bit (1), two ways to pick the second bit (0 or 1), two ways to pick the third bit (0 or 1), . . . two ways to pick the eighth bit (0 or 1). Product rule: Task 1 can be done in 127 = 128 ways. 9
  • 10.
    Task 2: Constructa string of length 8 that ends with 00. There are two ways to pick the first bit (0 or 1), two ways to pick the second bit (0 or 1), . . . two ways to pick the sixth bit (0 or 1), one way to pick the seventh bit (0), and one way to pick the eighth bit (0). Product rule: Task 2 can be done in 26 = 64 ways. 10 Inclusion-Exclusion
  • 11.
    Since there are128 ways to do Task 1 and 64 ways to do Task 2, does this mean that there are 192 bit strings either starting with 1 or ending with 00 ? No, because here Task 1 and Task 2 can be done at the same time. When we carry out Task 1 and create strings starting with 1, some of these strings end with 00. Therefore, we sometimes do Tasks 1 and 2 at the same time, so the sum rule does not apply. 11 Inclusion-Exclusion
  • 12.
    If we wantto use the sum rule in such a case, we have to subtract the cases when Tasks 1 and 2 are done at the same time. How many cases are there, that is, how many strings start with 1 and end with 00? There is one way to pick the first bit (1), two ways for the second, …, sixth bit (0 or 1), one way for the seventh, eighth bit (0). Product rule: In 25 = 32 cases, Tasks 1 and 2 are carried out at the same time. 12 Inclusion-Exclusion
  • 13.
    Since there are128 ways to complete Task 1 and 64 ways to complete Task 2, and in 32 of these cases Tasks 1 and 2 are completed at the same time, there are 128 + 64 – 32 = 160 ways to do either task. In set theory, this corresponds to sets A1 and A2 that are not disjoint. Then we have: |A1  A2| = |A1| + |A2| - |A1  A2| This is called the principle of inclusion-exclusion. 13 Inclusion-Exclusion
  • 14.
    Tree Diagrams How manybit strings of length four do not have two consecutive 1s?  Task 1 Task 2 Task 3 Task 4 (1st bit) (2nd bit) (3rd bit) (4th bit) 14 0 0 0 0 1 1 0 1 0 0 1 1 0 0 0 1 1 0 There are 8 strings.
  • 15.
    The Pigeonhole Principle Thepigeonhole principle: If (k + 1) or more objects are placed into k boxes, then there is at least one box containing two or more of the objects. Example 1: If there are 11 players in a soccer team that wins 12-0, there must be at least one player in the team who scored at least twice. Example 2: If you have 6 classes from Monday to Friday, there must be at least one day on which you have at least two classes. 15
  • 16.
    The generalized pigeonholeprinciple: If N objects are placed into k boxes, then there is at least one box containing at least N/k of the objects. Example 1: In our 60-student class, at least 12 students will get the same letter grade (A, B, C, D, or F). 16 The Pigeonhole Principle
  • 17.
    Example 2: Assumeyou have a drawer containing a random distribution of a dozen brown socks and a dozen black socks. It is dark, so how many socks do you have to pick to be sure that among them there is a matching pair? There are two types of socks, so if you pick at least 3 socks, there must be either at least two brown socks or at least two black socks. Generalized pigeonhole principle: 3/2 = 2. 17 The Pigeonhole Principle
  • 18.
    Permutations and Combinations Howmany ways are there to pick a set of 3 people from a group of 6? There are 6 choices for the first person, 5 for the second one, and 4 for the third one, so there are 654 = 120 ways to do this. This is not the correct result! For example, picking person C, then person A, and then person E leads to the same group as first picking E, then C, and then A. However, these cases are counted separately in the above equation. 18
  • 19.
    So how canwe compute how many different subsets of people can be picked (that is, we want to disregard the order of picking) ? To find out about this, we need to look at permutations. A permutation of a set of distinct objects is an ordered arrangement of these objects. An ordered arrangement of r elements of a set is called an r-permutation. 19 Permutations and Combinations
  • 20.
    Example: Let S= {1, 2, 3}. The arrangement 3, 1, 2 is a permutation of S. The arrangement 3, 2 is a 2-permutation of S. The number of r-permutations of a set with n distinct elements is denoted by P(n, r). We can calculate P(n, r) with the product rule: P(n, r) = n(n – 1)(n – 2) …(n – r + 1). (n choices for the first element, (n – 1) for the second one, (n – 2) for the third one…) 20 Permutations and Combinations
  • 21.
    Example: P(8, 3) =876 = 336  = (87654321)/(54321) General formula: P(n, r) = n!/(n – r)! Knowing this, we can return to our initial question: How many ways are there to pick a set of 3 people from a group of 6 (disregarding the order of picking)? 21 Permutations and Combinations
  • 22.
    An r-combination ofelements of a set is an unordered selection of r elements from the set. Thus, an r-combination is simply a subset of the set with r elements. Example: Let S = {1, 2, 3, 4}. Then {1, 3, 4} is a 3-combination from S. The number of r-combinations of a set with n distinct elements is denoted by C(n, r). Example: C(4, 2) = 6, since, for example, the 2- combinations of a set {1, 2, 3, 4} are {1, 2}, {1, 3}, {1, 4}, {2, 3}, {2, 4}, {3, 4}. 22 Permutations and Combinations
  • 23.
    How can wecalculate C(n, r)? Consider that we can obtain the r-permutation of a set in the following way: First, we form all the r-combinations of the set (there are C(n, r) such r-combinations). Then, we generate all possible orderings in each of these r- combinations (there are P(r, r) such orderings in each case). Therefore, we have: P(n, r) = C(n, r)P(r, r) 23 Permutations and Combinations
  • 24.
    C(n, r) =P(n, r)/P(r, r)  = n!/(n – r)!/(r!/(r – r)!)  = n!/(r!(n – r)!) Now we can answer our initial question: How many ways are there to pick a set of 3 people from a group of 6 (disregarding the order of picking)? C(6, 3) = 6!/(3!3!) = 720/(66) = 720/36 = 20 There are 20 different ways, that is, 20 different groups to be picked. 24 Permutations and Combinations
  • 25.
    Corollary: Let n andr be nonnegative integers with r  n. Then C(n, r) = C(n, n – r). Note that “picking a group of r people from a group of n people” is the same as “splitting a group of n people into a group of r people and another group of (n – r) people”. Please also look at proof on page 252. 25 Permutations and Combinations
  • 26.
    Example: A soccer clubhas 8 female and 7 male members. For today’s match, the coach wants to have 6 female and 5 male players on the grass. How many possible configurations are there? C(8, 6)  C(7, 5) = 8!/(6!2!)  7!/(5!2!)  = 2821  = 588 26 Permutations and Combinations
  • 27.
    Combinations 27 ) , ( ! )! ( ! )]! ( [ )! ( ! ) , ( r n C r r n n r n n r n n r n n C        This symmetry is intuitively plausible. For example, let us consider a set containing six elements (n = 6). Picking two elements and leaving four is essentially the same as picking four elements and leaving two. In either case, our number of choices is the number of possibilities to divide the set into one set containing two elements and another set containing four elements.
  • 28.
    Pascal’s Identity: Let nand k be positive integers with n  k. Then C(n + 1, k) = C(n, k – 1) + C(n, k). How can this be explained? What is it good for? 28 Combinations
  • 29.
    Imagine a setS containing n elements and a set T containing (n + 1) elements, namely all elements in S plus a new element a. Calculating C(n + 1, k) is equivalent to answering the question: How many subsets of T containing k items are there? Case I: The subset contains (k – 1) elements of S plus the element a: C(n, k – 1) choices. Case II: The subset contains k elements of S and does not contain a: C(n, k) choices. Sum Rule: C(n + 1, k) = C(n, k – 1) + C(n, k). 29 Combinations
  • 30.
    Pascal’s Triangle In Pascal’striangle, each number is the sum of the numbers to its upper left and upper right: 30 1 1 1 1 2 1 1 3 3 1 1 4 6 4 1 … … … … … …
  • 31.
    Since we haveC(n + 1, k) = C(n, k – 1) + C(n, k) and C(0, 0) = 1, we can use Pascal’s triangle to simplify the computation of C(n, k): 31 C(0, 0) = 1 C(1, 0) = 1 C(1, 1) = 1 C(2, 0) = 1 C(2, 1) = 2 C(2, 2) = 1 C(3, 0) = 1 C(3, 1) = 3 C(3, 2) = 3 C(3, 3) = 1 C(4, 0) = 1 C(4, 1) = 4 C(4, 2) = 6 C(4, 3) = 4 C(4, 4) = 1 k n Pascal’s Triangle
  • 32.
    Binomial Coefficients Expressions ofthe form C(n, k) are also called binomial coefficients. How come? A binomial expression is the sum of two terms, such as (a + b). Now consider (a + b)2 = (a + b)(a + b). When expanding such expressions, we have to form all possible products of a term in the first factor and a term in the second factor: (a + b)2 = a·a + a·b + b·a + b·b Then we can sum identical terms: (a + b)2 = a2 + 2ab + b2 32
  • 33.
    For (a +b)3 = (a + b)(a + b)(a + b) we have (a + b)3 = aaa + aab + aba + abb + baa + bab + bba + bbb (a + b)3 = a3 + 3a2 b + 3ab2 + b3 There is only one term a3 , because there is only one possibility to form it: Choose a from all three factors: C(3, 3) = 1. There is three times the term a2 b, because there are three possibilities to choose a from two out of the three factors: C(3, 2) = 3. Similarly, there is three times the term ab2 (C(3, 1) = 3) and once the term b3 (C(3, 0) = 1). 33 Binomial Coefficients
  • 34.
    This leads usto the following formula: 34 j n j j n n b a j n C b a       0 ) , ( ) ( With the help of Pascal’s triangle, this formula can considerably simplify the process of expanding powers of binomial expressions. For example, the fifth row of Pascal’s triangle (1 – 4 – 6 – 4 – 1) helps us to compute (a + b)4 : (a + b)4 = a4 + 4a3 b + 6a2 b2 + 4ab3 + b4 (Binomial Theorem) Binomial Coefficients