Chapter 3 Set Theory

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Transcript Chapter 3 Set Theory

Chapter 3
Set Theory
Yen-Liang Chen
Dept of Information Management
National Central University
1
3.1 Sets and subsets
 Definitions
– Element and set , Ex 3.1
– Finite set and infinite set, cardinality  A ,
Ex 3.2
– CD a subset, CD a proper subset
– C=D, two sets are equal
– Neither order nor repetition is relevant
for a general set
– null set, {}, 
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Subset relations
 AB
 x [xAxB]
 B
A
 x [xAxB]
 x  [xAxB]
 x  [(xA)(xB)]
 x [xA(xB)]
 x [xAxB]
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Subset relations
 AB
(ABBA)
(AB)(BA)
(A  B) (B  A)
 AB
AB AB
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Ex 3.5
5
Theorems 3.1. and 3.2

Theorem 3.1
–
–
–
–

If
If
If
If
AB
AB
AB
AB
and
and
and
and
BC,
BC,
BC,
BC,
then
then
then
then
AC,
AC,
AC,
AC,
Theorem 3.2
–  A. If A is not empty, then A.
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Power set
 For
any finite set A with  A =n, the
total number of subsets of A is 2n.
 Definition 3.4. the power set of A,
denoted as (A) is the collection of
all subsets of A.
 What is the power set of {1, 2,3 4}?
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Ex 3.10
Count the number of paths in the xy-plane
from (2,1) to (7,4)
 The number of paths sought here equals
the number of subsets A of {1,2,…,8},
where  A =3.

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Ex 3.11
Count the number of compositions of an
integer, say 7
 7=1+1+1+1+1+1+1, there are six plus
signs.

– Subset {1,4,6} 
(1+1)+1+(1+1)+(1+1)2+1+2+2
– Subset {1,2,5,6}
(1+1+1)+1+(1+1+1)3+1+3
– Subset {3,4,5,6}
1+1+(1+1+1+1+1)1+1+5

Consequently, there are 2m-1 compositions
for the value m.
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10
An important identity
C(n+1, r)= C(n, r)+C(n, r-1)
 Pascal’a triangle in Ex 3.14

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3.2 Set operations and the laws of
set theory

Definition 3.5.
–
–
–
–

AB={xxA  xB}
AB={xxA  xB}
AB={xxAB  xAB}
Ex 3.15
Definitions 3.6, 3.7, 3.8
– S, T are disjoint, written ST=
– The complement of A, denoted as A
– The relative complement of A in B, denoted BA
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Ex 3.18
13
Theorem 3.4
 The
following statements are
equivalent
– AB
– AB=B
– AB=A
– BA
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AB  AB=B AB=A





B(AB) for any sets
x(AB) 
(xA)(xB)
since AB,  (xB)
this means (AB)B
we conclude AB=B
AAB for any sets
 yA yAB (1)
 Since AB=B,
(1)yBy(AB)
 This means AAB
 we conclude
A=AB

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AB=A  B  A  AB
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17
A B  A B
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A(BC)=(AB)(AC)
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The Duality
 Definition
3.9 Let s be a statement dealing
with the equality of two set expressions. The
dual of s, denoted sd, is obtained from s by
replacing (1) each occurrence of  and U by U
and , respectively; and (2) each occurrence of
 and  by  and , respectively.
 Theorem 3.5. s is a theorem if and only if sd is
also a theorem.
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Three approaches to proof
 The
first approach to prove a theorem is by
element argument.
 The second is by Venn diagram, and
 the third is by membership table.
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Venn diagram to show
A B  A B
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Venn diagram to show
( A  B)  C  ( A  B)  C
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membership table
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Membership table for
A(BC)=(AB)(AC)
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Ex 3.20
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Ex 3.22
27
4
1
2
3
A={1,2}, B={2,3}, A∆B={1,3}, A´={3,4}, B´={1,4}
A´∆B={2, 4}= B´∆A = (A∆B)´
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Generalized DeMorgan’s Law
A A
i
i
iI
iI
A
i
iI

A
i
iI
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3.3. Counting and Venn diagrams
 Finite
sets A and B are disjoint if and only if
 A  B =  A +  B  , Figures 3.9 and 3.10
 Ex 3.25, If A and B are finite sets, then AB=
A+ B-AB , Figure 3.11
 When U is finite, we have
A B  A B  U  A B  U  A  B  A B
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Ex 3.26
 How
many gates have at least one of the
defects D1, D2, D3? How many are perfect?
 Figure 3.12 and Figure 3.13. If A, B and C are
finite sets, then ABC= A+ B+C-ABAC-BC + ABC
 When U is finite, we have
A B C  A B C  U  A B C
 U  A  B  C  A B  AC  B C  A B C
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3.4. A first world on probability
Let  be the sample space for an experiment. Each
subset A of , including the empty subset, is called an
event. Each element of  determines an outcome. If
=n, then Pr({a})=1/n and Pr(A)= A /n
 Ex 3.29, Ex 3.30, Ex 3.31
 Definition 3.11. For sets A and B, the Cartesian
product of A and B is denoted by AB and equals {(a,
b)a A , b  B}. We call the elements of AB
ordered pairs.

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Ex 3.33
 Suppose
we roll two fair dice.
 Consider the following event
– A: rolls a 6
– B: The sum of dice is at least 7
– C: Rolls an even sum
– D: The sum of the dice is 6 or less
 What
are P(A), P(B), P(C), P(D),
P(AB), P(CD)?
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Examples
 Ex
3.35. If we toss a fair coin four
times, what is the prob that we get
two heads and two tails?
 Ex 3.36. Among the letters
WYSIWYG, what is the prob that the
arrangement has both consecutive
W’s and Y’s? and the prob that the
arrangement starts and ends with W?
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3.5. The axioms of probability
 Ex
3.39. The outcomes of a sample space may
have different likelihoods
 A warehouse has 10 motors, three of
which are defective. We select two
motors.
– A: exactly one is defective
– B: at least one motor is defective
– C: both motors are defective
– D: Both motors are in good condition.
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The axioms of probability
 be the sample space for an experiment. If
A and B are any events, then
 Let
– Pr(A)0
– Pr()=1
– If A and B are disjoint, Pr(A  B )=Pr(A) + Pr(B)
 Theorem
3.7.
Pr(A)  1  Pr(A)
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Ex 3.40

The letters PROBABILITY are arranged in a
random manner. Determine the prob of
the following event: The first and last
letters are different.
– Neither B nor I appears at the start or finish.
 (7)(9!/2!2!)(6)
– Only B appears at the start or finish.
 (2)(7)(9!/2!)
– One of B is used at the start and I as the other.
 (2)(9!)
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Ex 3.41

The prob that our team can win any
tournament is 0.7. Suppose we need to
play eight tournaments. Consider the
following cases:
– Win all eight games. (0.3)8
– Win exactly five of the eight. C(8, 5)(0.7)5(0.3)3
– Win at least one. 1-(0.3)8

If there are n trials and each trial has probability p of
success and 1-p of failure, the probability that there
are k successes among these n trials is  n  p (1  p)
k
n k
k 
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Theorem 3.8
 Pr(AB)
=Pr(ABc) + Pr(B)
= Pr(A) + Pr(B)- Pr(AB )
 Ex 3.42
– What is the prob that the card drawn is
a club and the value is between 3 and 7.
 Ex
3.43
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Theorem 3.9.

Pr(ABC)= Pr(A)+ Pr(B)+Pr(C)-Pr(AB)Pr(AC)-Pr(BC) + Pr(ABC)
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