1. Lecture 4: Predicates and Quantifiers; Sets.
Zeph Grunschlag
Copyright © Zeph Grunschlag,

2. Announcements
HW1 due now L4

3. Agenda Predicates and Quantifiers Sets Existential Quantifier 
Universal Quantifier 
Sets
Curly brace notation “{ … }”
Cardinality “| … |”
Element containment 
Subset containment 
Empty set { } = 
Power set P(S ) = 2S
N-tuples “( … )” and Cartesian product  L4

4. If Zeph is an octopus then Zeph has 8 limbs.
Motivating example
Consider the compound proposition:
If Zeph is an octopus then Zeph has 8 limbs.
Q1: What are the atomic propositions and how do they form this proposition.
Q2: Is the proposition true or false?
Q3: Why?
Question: why is the last a contingency? L4

5. Motivating example
A1: Let p = “Zeph is an octopus” and q = “Zeph has 8 limbs”. The compound proposition is represented by p q.
A2: True!
A3: Conditional always true when p is false!
Q: Why is this not satisfying?
Question: why is the last a contingency? L4

6. For all x, if x is an octopus then x has 8 limbs.
Motivating example
A: We wanted this to be true because of the fact that octopi have 8 limbs and not because of some (important) non-semantic technicality in the truth table of implication.
But recall that propositional calculus doesn’t take semantics into account so there is no way that p could impact on q or affect the truth of pq.
Logical Quantifiers help to fix this problem. In our case the fix would look like:
For all x, if x is an octopus then x has 8 limbs.
Then as a special case of x = Zeph, we would be able to conclude that pq is indeed true in the way hoped for. L4

7. “For all x, if x is an octopus then x has 8 limbs.”
Motivating example
Expressions such as the previous are built up from propositional functions –statements that have a variable or variables that represent various possible subjects. Then quantifiers are used to bind the variables and create a proposition with embedded semantics. For example:
“For all x, if x is an octopus then x has 8 limbs.”
there are two atomic propositional functions
P (x) = “x is an octopus”
Q (x) = “x has 8 limbs”
whose conditional P (x) Q (x) is formed and is bound by “For all x ”.
Question: why is the last a contingency? L4

8. Semantics
If logical propositions are to have meaning, they need to describe something. Up to now, propositions such as “Johnny is tall”, “Debbie is 5 years old”, and “Andre is immature” had no intrinsic meaning. Either they are true or false, but no more.
In order to endow such propositions with meaning, we need to have a universe of discourse, i.e. a collection of subjects (or nouns) about which the propositions relate.
Q: What is the universe of discourse for the three propositions above? L4

9. Semantics A: There are many answers. Here are some:
Johnny, Debbie and Andre (this is also the smallest correct answer)
People in the world
Animals
Java: The Java analog of a universe of discourse is a type. There are two categories of types in Java: reference types which consist of objects and arrays, and primitive types like int, boolean, char, etc. Examples of Java “universes” are:
int, char, int[][], Object, String, java.util.LinkedList, Exception, etc.
From now on, all of our propositions will be descriptions of objects certain universes of discourse. Usually, the universe of discourse won’t be spelled out, and will be obvious. However, from time time we’ll need to spell out the universe precisely for propositions to have a well defined truth value. L4

10. Predicates
A predicate is a property or description of subjects in the universe of discourse. The following predicates are all italicized :
Johnny is tall.
The bridge is structurally sound.
17 is a prime number.
Java: predicates are boolean-valued method calls-
someLinkedList.isEmpty()
isPrime(17) L4

11. Propositional Functions
By taking a variable subject denoted by symbols such as x, y, z, and applying a predicate one obtains a propositional function (or formula). When an object from the universe is plugged in for x, y, etc. a truth value results:
x is tall. …e.g. plug in x = Johnny
y is structurally sound. …e.g. plug in y = GWB
n is a prime number. …e.g. plug in n = 111
Java: propositional functions are boolean methods, rather than particular calls.
boolean isEmpty(){…} //in LinkedList
boolean isPrime(int n){…} L4

12. Multivariable Predicates
Multivariable predicates generalize predicates to allow descriptions of relationships between subjects. These subjects may or may not even be in the same universe of discourse. For example:
Johnny is taller than Debbie.
17 is greater than one of 12, 45.
Johnny is at least 5 inches taller than Debbie.
Q: What universes of discourse are involved? L4

13. Multivariable Predicates
A: Again, many correct answers. The most obvious answers are:
For “Johnny is taller than Debbie” the universe of discourse of both variables is all people in the universe
For “17 is greater than one of 12, 45” the universe of discourse of all three variables is Z (the set of integers)
For “Johnny is at least 5 inches taller than Debbie” the first and last variable have people as their universe of discourse, while the second variable has R (the set of real numbers). L4

14. Multivariable Propositional Functions
The multivariable predicates, together with their variables create multivariable propositional functions. In the above examples, we have the following generalizations:
x is taller than y
a is greater than one of b, c
x is at least n inches taller than y
In Java, a multivariable predicate is a boolean method with several arguments:
tallerByNumInches(Person x, double n, Person y)
{ … } L4

15. Quantifiers There are two quantifiers Existential Quantifier
“” reads “there exists”
Universal Quantifier
“” reads “for all”
Each is placed in front of a propositional function and binds it to obtain a proposition with semantic value.
Mnemonics:
 -- reverse E signifies “there Exists”
 -- upside-down A signifies “for All” L4

16. Existential Quantifier
“x P (x)” is true when an instance can be found which when plugged in for x makes P (x) true
Like disjunctioning over entire universe x P (x )  P (x1) P (x2) P (x3)  … L4

17. Existential Quantifier. Example
Consider a universe consisting of
Leo: a lion
Jan: an octopus with all 8 tentacles
Bill: an octopus with only 7 tentacles
And recall the propositional functions
P (x) = “x is an octopus”
Q (x) = “x has 8 limbs”
x ( P (x) Q (x) )
Q: Is the proposition true or false? L4

18. Existential Quantifier. Example
A: True. Proposition is equivalent to
(P (Leo)Q (Leo) )(P (Jan) Q (Jan) )(P(Bill)Q (Bill) )
P (Leo) is false because Leo is a Lion, not an octopus, therefore the conditional
P (Leo) Q (Leo) is true, and the disjunction is true.
Leo is called a positive example. L4

19. The Universal Quantifier
“x P (x)” true when every instance of x makes P (x) true when plugged in
Like conjunctioning over entire universe x P (x )  P (x1) P (x2)  P (x3)  … L4

20. Universal Quantifier. Example
Consider the same universe and propositional functions as before.
 x ( P (x) Q (x ) )
Q: Is the proposition true or false? L4

21. Universal Quantifier. Example
A: False. The proposition is equivalent to
(P (Leo)Q (Leo))(P (Jan)Q (Jan))(P (Bill)Q (Bill))
Bill is the counter-example, i.e. a value making an instance –and therefore the whole universal quantification– false.
P (Bill) is true because Bill is an octopus, while Q (Bill) is false because Bill only has 7 tentacles, not 8. Thus the conditional P (Bill)Q (Bill) is false since TF gives F, and the conjunction is false. L4

22. Illegal Quantifications
Once a variable has been bound, we cannot bind it again. For example the expression
x ( x P (x) )
is nonsensical. The interior expression (x P (x)) bounded x already and therefore made it unobservable to the outside. Going back to our example, the English equivalent would be:
Everybody is an everybody is an octopus. L4

23. Multivariate Quantification
Quantification involving only one variable is fairly straightforward. Just a bunch of OR’s or a bunch of AND’s.
When two or more variables are involved each of which is bound by a quantifier, the order of the binding is important and the meaning often requires some thought. L4

24. Parsing Multivariate Quantification
When evaluating an expression such as
x y z P (x,y,z )
translate the proposition in the same order to English:
There is an x such that for all y there is a z such that P (x,y,z) holds. L4

25. There is an x such that for all y there is a z such that y - x ≥ z.
Parsing Example
P (x,y,z ) = “y - x ≥ z ”
There is an x such that for all y there is a z such that y - x ≥ z.
There is some number x which when subtracted from any number y results in a number bigger than some number z.
Q: If the universe of discourse for x, y, and z is the natural numbers {0,1,2,3,4,5,6,7,…} what’s the truth value of xy z P (x,y,z )? L4

26. Parsing Example A: True.
For any “exists” we need to find a positive instance.
Since x is the first variable in the expression and is “existential”, we need a number that works for all other y, z. Set x = 0 (want to ensure that y -x is not too small).
Now for each y we need to find a positive instance z such that y - x ≥ z holds. Plugging in x = 0 we need to satisfy y ≥ z so set z := y.
Q: Did we have to set z := y ?
“:=” means that we are assigning the value of y to z (like the assignment symbol “=” in Java) L4

27. Parsing Example
A: No. Could also have used the constant z := 0. Many other valid solutions.
Q: Isn’t it simpler to satisfy
x y z (y - x ≥ z )
by setting x := y and z := 0 ? L4

28. Parsing Example
A: No, this is illegal ! The existence of x comes before we know about y. I.e., the scope of x is higher than the scope of y so as far as y can tell, x is a constant and cannot affect x.
A Java example helps explain this point. To evaluate x y Q (x,y ) might do the following. L4

29. Parsing Example —Java boolean exists_x_forAll_y(){
for(int x=firstInt; x<=lastInt; x++){
if (forAll_y(x)) return true; }
return false;
boolean forAll_y(int x){
for(int y=firstInt; y<=lastInt; y++){
if ( !Q(x,y) ) return false;
return true;
The variables firstInt ans lastInt denote first and last possible int’s, which turn out to respectively be -231 = and 231-1= (See section on 2’s complement.)
Notice that Java makes it impossible to change value of x which is passed by value into “for all” method. This is exactly the behavior we would like to have! L4

30. Order matters
Set the universe of discourse to be all natural numbers {0, 1, 2, 3, … }.
Let R (x,y ) = “x < y”.
Q1: What does x y R (x,y ) mean?
Q2: What does y x R (x,y ) mean? L4

31. Order matters R (x,y ) = “x < y” A1: x y R (x,y ):
“All numbers x admit a bigger number y ”
A2: y x R (x,y ):
“Some number y is bigger than all x”
Q: What’s the true value of each expression? L4

32. Order matters A: 1 is true and 2 is false.
x y R (x,y ): “All numbers x admit a bigger number y ” --just set y = x + 1
y x R (x,y ): “Some number y is bigger than all numbers x” --y is never bigger than itself, so setting x = y is a counterexample
Q: What if we have two quantifiers of the same kind? Does order still matter? L4

33. Order matters –but not always
A: No! If we have two quantifiers of the same kind order is irrelevent.
x y is the same as y x because these are both interpreted as “for every combination of x and y…”
x y is the same as y x because these are both interpreted as “there is a pair x , y…”
Try to see why this is with some Java code (nested forAll’s and nested exist’s) L4

34. Logical Equivalence with Formulas
DEF: Two logical expressions possibly involving propositional formulas and quantifiers are said to be logically equivalent if no-matter what universe and what particular propositional formulas are plugged in, the expressions always have the same truth value.
EG: x y Q (x,y ) and y x Q (y,x ) are equivalent –names of variables don’t matter.
EG: x y Q (x,y ) and y x Q (x,y ) are not! L4

35. DeMorgan Revisited Recall DeMorgan’s identities:
Conjunctional negation:
(p1p2…pn)  (p1p2…pn)
Disjunctional negation:
(p1p2…pn)  (p1p2…pn)
Since the quantifiers are the same as taking a bunch of AND’s () or OR’s () we have:
Universal negation:
 x P(x )  x P(x )
Existential negation:
 x P(x )  x P(x ) L4

36. x y ( x 2  y )  x y x 2 > y
Negation Example
Compute:  x y x2  y
In English, we are trying to find the opposite of “every x admits a y greater or equal to x’s square”. The opposite is that “some x does not admit a y greater or equal to x’s square”
Algebraically, one just flips all quantifiers from  to  and vice versa, and negates the interior propositional function. In our case we get:
x y ( x 2  y )  x y x 2 > y
Note that  x y x2  y
is the same as  ( x y x2  y ) L4

37. Blackboard Exercises Section 1.3
1.3.41) Show that the following are logically equivalent:
(x A(x ))(x B(x ))
x,y A(x )B(y )
Hint: To get started it’s useful to plug in examples for A and B.
E.g. could try letting A(x) = “x likes Christina Aguilera” and B(x) = “x likes Britney Spears” L4

38. Blackboard Exercises Section 1.3
Need to show that
(x A(x ))(x B(x ))x,y A(x )B(y )
is a tautology, so LHS and RHS must always have same truth values.
Hint: To get started it’s useful to plug in examples for A and B.
E.g. could try letting A(x) = “x likes Christina Aguilera” and B(x) = “x likes Britney Spears” L4

39. Blackboard Exercises Section 1
Blackboard Exercises Section 1.3 (x A(x ))(x B(x ))x,y A(x )B(y )
CASE I) Assuming LHS true show RHS true.
Either x A(x ) true OR x B(x ) true
Case I.A) For all x, A(x ) true.
As (T  anything) = T, we can set
anything = B(y) and obtain
For all x and y, A(x )B(y ) –the RHS!
Case I.B) For all x, B(x ) true… similar to case (I.A)
Hint: To get started it’s useful to plug in examples for A and B.
E.g. could try letting A(x) = “x likes Christina Aguilera” and B(x) = “x likes Britney Spears” L4

40. Blackboard Exercises Section 1
Blackboard Exercises Section 1.3 (x A(x ))(x B(x ))x,y A(x )B(y )
CASE II) Assume LHS false, show RHS false.
Both x A(x ) false AND x B(x ) false.
Thus x  A(x ) true AND x  B(x ) true.
Thus there is an example x1 for which A(x1) is false and an example x2 for which B(x2) is false.
As F  F = F, we have A(x1)B(x2) false.
Setting x = x1 and y = x2 gives a counterexample to x,y A(x )B(y ) showing the RHS false //QED
Hint: To get started it’s useful to plug in examples for A and B.
E.g. could try letting A(x) = “x likes Christina Aguilera” and B(x) = “x likes Britney Spears” L4

41. Section 1.4: Sets DEF: A set is a collection of elements.
This is another example where mathematics must start at the level of intuition. Sets are the basic data structure out of which most mathematical theories are built. For many years mathematicians hoped that sets could be defined directly from logic, thus giving a full-proof foundation to Mathematics, when compared to other sciences. Effort failed! L4

42. Sets Curly braces “{“ and “}” are used to denote sets.
Java note: In Java curly braces denote arrays, a data-structure with inherent ordering. Mathematical sets are unordered so different from Java arrays. Java arrays require that all elements be of the same type. Mathematical sets don’t require this, however. EG:
{ 11, 12, 13 }
{ , , }
{ , , , 11, Leo } L4

43. Sets
A set is defined only by the elements which it contains. Thus repeating an element, or changing the ordering of elements in the description of the set, does not change the set itself:
{ 11, 11, 11, 12, 13 } = { 11, 12, 13 }
{ , , } = { , , } L4

44. Standard Numerical Sets
The natural numbers:
N = { 0, 1, 2, 3, 4, … }
The integers:
Z = { … -3, -2, -1, 0, 1, 2, 3, … }
The positive integers:
Z+ = {1, 2, 3, 4, 5, … }
The real numbers: R --contains any decimal number of arbitrary precision
The rational numbers: Q --these are decimal numbers whose decimal expansion repeats
Q: Give examples of numbers in R but not Q. L4

45. Standard Numerical Sets

46. -Notation
The Greek letter “” (epsilon) is used to denote that an object is an element of a set. When crossed out “” denotes that the object is not an element.”
EG: 3  S reads:
“3 is an element of the set S ”.
Q: Which of the following are true:
3  R
-3  N
-3  R
0  Z+
x xR  x2=-5 L4

47. -Notation A: 1, 3 and 4 3  R. True: 3 is a real number.
-3  N. False: natural numbers don’t contain negatives.
-3  R. True: -3 is a real number.
0  Z+. True: 0 isn’t positive.
x xR  x2=-5 . False: square of a real number is non-neg., so can’t be -5. L4

48. -Notation
DEF: A set S is said to be a subset of the set T iff every element of S is also an element of T. This situation is denoted by
S  T
A synonym of “subset” is “contained by”.
Definitions are often just a means of establishing a logical equivalence which aids in notation. The definition above says that:
S  T  x (xS )  (xT )
We already had all the necessary concepts, but the “” notation saves work.
Note that we don’t need to parenthesize x (xS )  (xT ) as x [(xS )  (xT )] because no other interpretation would result in a valid proposition. E.g. isn’t [x (xS )]  (xT ) valid because x remains an unbound variable. On the other hand x [ [ x (xS ) ]  (x T )] is a valid formula, though very confusing. L4

49. -Notation
When “” is used instead of “”, proper containment is meant. A subset S of T is said to be a proper subset if S is not equal to T. Notationally:
S  T  S T  x (x  S  xT )
Q: What algebraic symbol is  reminiscent of? L4

50. -Notation
A:  is to , as < is to . L4

51. The Empty Set
The empty set is the set containing no elements. This set is also called the null set and is denoted by: {}  L4

52. Subset Examples Q: Which of the following are true: N  R Z  N -3  R
  
   L4

53. Subset Examples A: 1, 4 and 5 N  R. All natural numbers are real.
Z  N. Negative numbers aren’t natural.
-3  R. Nonsensical. -3 is not a subset but an element! (This could have made sense if we viewed -3 as a set –which in principle is the case– in this case the proposition is false).
{1,2}  Z+. This actually makes sense. The set {1,2} is an object in its own right, so could be an element of some set; however, {1,2} is not a number, therefore is not an element of Z.
  . Any set contains itself.
  . No set can contain itself properly. L4

54. Cardinality
The cardinality of a set is the number of distinct elements in the set. |S | denotes the cardinality of S.
Q: Compute each cardinality.
|{1, -13, 4, -13, 1}|
|{3, {1,2,3,4}, }|
|{}|
|{ {}, {{}}, {{{}}} }| L4

55. Cardinality
Hint: After eliminating the redundancies just look at the number of top level commas and add 1 (except for the empty set). A:
|{1, -13, 4, -13, 1}| = |{1, -13, 4}| = 3
|{3, {1,2,3,4}, }| = 3. To see this, set S = {1,2,3,4}. Compute the cardinality of {3,S, }
|{}| = || = 0
|{ {}, {{}}, {{{}}} }| = |{ , {}, {{}}| = 3 L4

56. Cardinality
DEF: The set S is said to be finite if its cardinality is a nonnegative integer. Otherwise, S is said to be infinite.
EG: N, Z, Z+, R, Q are each infinite.
Note: We’ll see later that not all infinities are the same. In fact, R will end up having a bigger infinity-type than N, but surprisingly, N has same infinity-type as Z, Z+, and Q. L4

57. Power Set DEF: The power set of S is the set of all subsets of S.
Denote the power set by P (S ) or by 2s .
The latter weird notation comes from the following.
Lemma: | 2s | = 2|s|
We’ll prove this lemma later. L4

58. Power Set –Example To understand the previous fact consider
Enumerate all the subsets of S :
0-element sets: {}
1-element sets: {1}, {2}, {3} +3
2-element sets: {1,2}, {1,3}, {2,3} +3
3-element sets: {1,2,3} +1
Therefore: | 2s | = 8 = 23 = 2|s|
Why is this not a proof of the lemma on previous page? L4

59. Ordered n-tuples
Notationally, n-tuples look like sets except that curly braces are replaced by parentheses:
( 11, 12 ) –a 2-tuple aka ordered pair
( , , ) –a 3-tuple
( , , , 11, Leo ) –a 5-tuple
Java: n -tuples are similar to Java arrays “{…}”, except that type-mixing isn’t allowed in Java. L4

60. Ordered n-tuples
As opposed to sets, repetition and ordering do matter with n-tuples.
(11, 11, 11, 12, 13)  ( 11, 12, 13 )
( , , )  ( , , ) L4

61. Cartesian Product
The most famous example of 2-tuples are points in the Cartesian plane R2. Here ordered pairs (x,y) of elements of R describe the coordinates of each point. We can think of the first coordinate as the value on the x-axis and the second coordinate as the value on the y-axis.
DEF: The Cartesian product of two sets A and B –denoted by A B– is the set of all ordered pairs (a, b) where aA and bB .
Q: Describe R2 as the Cartesian product of two sets. L4

62. Cartesian Product
A: R2 = RR. I.e., the Cartesian plane is formed by taking the Cartesian product of the x-axis with the y-axis.
One can generalize the Cartesian product to several sets simultaneously.
Q: If A = {1,2}, B = {3,4}, C = {5,6,7}
what is A B C ? L4

63. | A1  A2  … An | = |A1||A2| … |An|
Cartesian Product
A: A = {1,2}, B = {3,4}, C = {5,6,7}
A B C =
{ (1,3,5), (1,3,6), (1,3,7),
(1,4,5), (1,4,6), (1,4,7),
(2,3,5), (2,3,6), (2,3,7),
(2,4,5), (2,4,6), (2,4,7) }
Lemma: The cardinality of the Cartesian product is the product of the cardinalities:
| A1  A2  … An | = |A1||A2| … |An|
Q: What does S equal? L4

64. Cartesian Product A: From the lemma: |S | = |||S | = 0|S | = 0
There is only one set with no elements –the empty set– therefore, S must be the empty set .
One can also check this directly from the definition of the Cartesian product. L4

65. Blackboard Exercise Section 1.4
Prove the following:
If A  B and B  C then A  C . L4

66. Illegal Quantifications
Q: For those familiar with Calculus, what is a similar situation?
A: It’s like trying to integrate a definite integral.
EG:
(What was probably meant was to evaluate an antiderivative of x 2 at 0.5) L4