The Grammar of Mathematics: Reading and Writing Sets and Logic
0. Key points
Section titled “0. Key points”- Mathematical prose is written using only two vocabularies: sets and logic. These are not separate subjects. The correspondences with “and”, with “or”, and with “implies” are exact.
- A proof of a set equality can always be split into the two inclusions and (Proposition 3.4). Whenever you are unsure how to begin a proof, return to this.
- ” implies ” is not a statement of causation. If is false, the implication is true. This convention is what allows a sentence such as “every element of the empty set exceeds ” to be handled without contradiction (Proposition 3.6).
- De Morgan’s laws wear three faces — one in propositional logic, one for sets, one for quantifiers — but there is only one law underneath (Lemma 4.3, Theorem 4.4, Corollary 5.6).
- Negating and is the mechanical operation of pushing the negation sign inward while interchanging and (Theorem 5.3). The negation of an - statement is produced by this procedure alone.
- “Sufficient condition” and “necessary condition” merely name the two directions of an arrow, and they say exactly what an inclusion of truth sets says (Proposition 6.3).
1. Motivation — what to rely on when intuition breaks
Section titled “1. Motivation — what to rely on when intuition breaks”If the conventions of mathematical language are taught as mere etiquette, it is impossible to see why so much care is needed. This section gives one episode in which the need actually arose.
Until the first half of the nineteenth century, a function was something one pictured as a graph. “A continuous function admits a tangent line except at scattered points” was, to the mathematicians of that era, beyond doubt. Then in 1872 Weierstrass showed that a function of the form
(with , with an odd natural number, and with ) is continuous at every real and yet differentiable at no point whatsoever. Something that cannot be drawn stood there as a formula. At that moment it became necessary to fix the meanings of “continuous” and “differentiable” by sentences rather than by pictures.
Around the same time Cantor began comparing the sizes of infinite sets, and the word “set” itself came under pressure to be made precise. By the end of the nineteenth century a style had been established: write a mathematical assertion as a finite string of symbols, and decide its truth from the written form alone. The vocabulary used in that style is the vocabulary of sets and logic.
By the end of this article you will be able to answer questions as elementary as the following.
- In a class containing no students at all, is “every student in the class is at least three metres tall” true or false?
- “If then ” is true, yet its converse is false. Why? What exactly is to ?
- “For every real number there is a larger real number” and “there is a real number larger than every real number” — where, written in symbols, do these differ?
2. Propositions and logical connectives
Section titled “2. Propositions and logical connectives”2.1. Propositions
Section titled “2.1. Propositions”Definition 2.1(Proposition)
A proposition is an assertion that is determined to be exactly one of true or false. When a proposition is true we say that its truth value is ; when it is false, that its truth value is .
The phrase “determined to be exactly one of” is doing real work. “This sentence is false” is contradictory whether taken as true or as false, so it is not a proposition. "" is not a proposition either, since its truth is undetermined until we say what is; assertions containing variables are treated as predicates in Definition 5.1.
Strictly speaking, describing a proposition as “an assertion determined to be true or false” is not a complete definition, since it does not explain what an assertion is. Mathematical logic first defines formulas as strings of symbols by finitely many rules, and then separately specifies a procedure that assigns truth values to them. This article works at the practical level just short of that. The move into formalization itself is discussed in Incompleteness theorems.
2.2. Four connectives and truth tables
Section titled “2.2. Four connectives and truth tables”Definition 2.3(Logical connectives)
Given propositions and , we define the new propositions (not ), ( and ), ( or ), (if then ), and ( and are equivalent) by the following table.
| T | T | F | T | T | T | T |
| T | F | F | F | T | F | F |
| F | T | T | F | T | T | F |
| F | F | T | F | F | T | T |
This table is the definition. The meaning of a connective is fixed by these four rows and not by the nuances of ordinary speech. Two points in particular depart from everyday usage.
- “Or” is not exclusive. If and are both true, then is true. This is unlike the everyday choice “coffee or tea”. To say that both cannot hold, write .
- “Implies” is not causal. If is false, then is true whatever may be. “If then Mount Fuji is at sea level” is, in the mathematical sense, a true proposition.
Discomfort at the second point is natural. Read not as asserting a connection between and , but as asserting only that the situation ” holds while fails” does not occur. Indeed, as Proposition 2.4 shows, has the same meaning as . Adopting this reading, we automatically obtain the convenient convention that an assertion about all members of a collection is true when the collection has no members (Proposition 3.6).
Proposition 2.4(Reformulations of implication)
For all propositions and , the following three propositions always take the same truth value.
The third is called the contrapositive of . Moreover, and always take the same truth value.
Proof(Proposition 2.4)
Following the table in Definition 2.3, we write out all four combinations of truth values of and .
| T | T | T | T | T | F | F |
| T | F | F | F | F | T | T |
| F | T | T | T | T | F | F |
| F | F | T | T | T | F | F |
We check each row. In row 1, is true and is true, so is T by row 1 of the table; is F, so ; and is F and is F, so is . In row 2, is true and is false, so is F, , and is . In rows 3 and 4, is false, so is T; is true, so is T; and is T because its conclusion is true.
Thus the three columns , and agree in all four rows. The column likewise agrees with the column in all four rows.
The availability of the contrapositive pays off directly in the practice of proof. Proving “if is even then is even” head-on is awkward, but the contrapositive “if is odd then is odd” requires only setting and computing . (For how this lemma is used in the proof that is irrational, see if a square is even so is its root(Lemma 7.4)[Techniques of Proof].)
Example 2.5(Converse, inverse and contrapositive)
Let be a real number, let be "", and let be "".
- is true, since gives .
- The converse is false. Taking makes true and false, which is row 2 of the table in Definition 2.3, so is F.
- The inverse is also false, since for the antecedent is true while is false.
- The contrapositive is true: if then cannot be . As Proposition 2.4 guarantees, this is the same as the truth of .
The converse and the inverse are contrapositives of each other, so, as we have just seen, they share their truth value.
3. Basic notions about sets
Section titled “3. Basic notions about sets”3.1. Elements and extensionality
Section titled “3.1. Elements and extensionality”Definition 3.1(Set and element)
A set is a collection of objects such that, for any object , whether or not belongs to it is uniquely determined. We write to say that belongs to the set , and call an element (or member) of . Non-membership is written .
There are two ways to specify a set: by listing all its elements, as in , and by comprehension, that is by carving it out with a condition, as in . Here , and we do not include .
Axiom 3.2(Principle of extensionality)
For sets and we stipulate
That is, a set is determined by nothing but which elements it has.
This is a stipulation, not a theorem. From it, it follows that a set has neither order nor repetition. Indeed and both satisfy ” belongs precisely when is or ”, so they are equal sets by Axiom 3.2.
Definition 3.3(Subset)
For sets and we define
and say that is a subset of . If moreover and , we say that is a proper subset of and write .
The symbols and are different things: expresses membership, expresses inclusion. For , the statement is true while is meaningless ( is not a set); and is true while is false, because the elements of are and , not .
Proposition 3.4(Set equality is double inclusion)
For sets and ,
Proof(Proposition 3.4)
By Axiom 3.2, is equivalent to “for every , ”. It therefore suffices to see that, for each ,
take the same truth value. Put for and for and consult the table in Definition 2.3: is T exactly in row 1 (both T) and row 4 (both F). On the other hand is F in row 2, where is F, and F in row 3, where is F, while in rows 1 and 4 both implications are T and so the conjunction is T. Hence the two agree in all four rows.
Consequently “for every , ” is equivalent to “for every , ” together with “for every , ”. By Definition 3.3 this is precisely and .
This proposition supplies the proof pattern used most often not only in this article but in all of mathematics. On seeing a set equality, split it into two inclusions and write each in the form “assume left-hand side and derive right-hand side”. This is called element chasing.
3.2. The empty set and power sets
Section titled “3.2. The empty set and power sets”Definition 3.5(Empty set and power set)
A set with no elements at all is called the empty set and is written ; that is, for every .
For a set , the set
consisting of all subsets of is called the power set of .
Proposition 3.6(Basic properties of the empty set)
(1) For every set we have .
(2) The empty set is unique: if and are sets with no elements, then .
Proof(Proposition 3.6)
(1) By Definition 3.3, what must be shown is “for every , ”. Take arbitrary; by Definition 3.5, is false. Looking at the table in Definition 2.3, in the rows with a false antecedent (rows 3 and 4) the value of is T. Hence is true regardless of , and holds.
(2) Suppose and both have no elements. The same argument as in (1) gives and : since is always false, is always true, and likewise is always true. By Proposition 3.4, .
An assertion that is automatically true because its antecedent never holds — as in the proof of (1) — is said to be vacuously true. The claim mentioned at the outset, that in a class with no students every student is at least three metres tall, has the same structure and is true: since not a single student can be produced as a counterexample, there is no way to make the assertion false.
Example 3.7(Writing out a power set)
Let . We enumerate the subsets exhaustively, grouped by their number of elements.
- elements:
- element:
- elements:
- elements:
Therefore
and the number of elements of is . Note that occurs by part (1) of Proposition 3.6, and that itself occurs because .
Theorem 3.8(Cardinality of a power set)
If is a finite set with elements, then has elements.
Proof(Theorem 3.8)
Label the elements of as (so that whenever ). Let
be the set of all - strings of length . Define a map from to by setting, for ,
For each exactly one of and holds (Definition 3.1), so is uniquely determined.
We show that is injective. Suppose satisfy . Every equals for some , and since the -th entries agree, "" and "" either both hold or both fail. For , the inclusions and give and . Hence for every , and Axiom 3.2 yields .
We show that is surjective. Given , put . Then , and by construction holds exactly when , so .
Therefore and have the same number of elements. The elements of are formed by choosing each entry independently from possibilities, so there are of them. Hence has elements.
Even when is infinite, one can prove that is “strictly larger” than (Cantor's theorem(Theorem 7.1)[濃度と無限]). This is the counterpart of in the finite case, but its proof rests on the diagonal argument rather than on counting. See Cardinality and infinity for details. An alternative proof of Theorem 3.8 by induction on is treated as an example in Proof techniques.
4. Operations on sets
Section titled “4. Operations on sets”4.1. Definitions and their correspondence with connectives
Section titled “4.1. Definitions and their correspondence with connectives”From here on we fix a set containing all objects under consideration and call it the universal set. Every set we handle is a subset of .
Definition 4.1(Union, intersection, difference, complement)
For we define
When we say that and are disjoint.
As the definitions make plain, the operations on sets are restatements of the logical connectives. The following table of correspondences is the backbone of the whole article.
| Sets | Condition on | Logic |
|---|---|---|
| and | ||
| or | ||
| and | with | |
| if then | ||
| and are equivalent |
Because of this correspondence, each identity proved in logic hands us an identity about sets. We carry out that procedure explicitly below.
The four regions of the figure are: ① is , ② is , ③ is , and ④ is . Any lies in exactly one of these four, according to the combination of whether and whether .
4.2. The distributive law
Section titled “4.2. The distributive law”Theorem 4.2(Distributive law)
For ,
Proof(Theorem 4.2)
By Proposition 3.4 we prove two inclusions.
() Let . By Definition 4.1, and . From the latter, or .
- Case : combined with this gives , hence .
- Case : combined with this gives , hence .
In either case , so .
() Let . Then or .
- Case : here and . From we get , so .
- Case : here and . From we get , so .
In either case , so .
Both inclusions being established, Proposition 3.4 gives the equality.
The other distributive law, , is proved by the same pattern. So that you can work it through yourself, it has been left to Exercise 7.2.
4.3. De Morgan’s laws
Section titled “4.3. De Morgan’s laws”Lemma 4.3(De Morgan's laws (propositional form))
For all propositions and , the propositions and always take the same truth value. Likewise and always take the same truth value.
Proof(Lemma 4.3)
Following the table in Definition 2.3, we write out the four cases.
| T | T | T | F | F | T | F | F |
| T | F | T | F | F | F | T | T |
| F | T | T | F | F | F | T | T |
| F | F | F | T | T | F | T | T |
For instance in row 2, is T and is F, so is T and its negation is F; on the other side is F, so is F, and the two agree. In the same row is F, its negation is T, and , so these agree as well. The remaining three rows are as tabulated.
The column agrees with the column , and the column agrees with the column , in all four rows.
Theorem 4.4(De Morgan's laws (set form))
For ,
Proof(Theorem 4.4)
We prove the first identity. Take arbitrary and put for the proposition "" and for "". Using the definitions in Definition 4.1, and Lemma 4.3 at the fourth line, the following equivalences hold in turn.
Since for every , Axiom 3.2 gives .
The second identity is proved by the same chain: , and by the second half of Lemma 4.3 we have , which says or , that is . Hence Axiom 3.2 gives .
The first half of Theorem 4.4 can also be checked using the four regions of the figure following Definition 4.1. Tabulating, for each region, whether a point lies in each side, we obtain the following (○ means “belongs”, × means “does not belong”).
| Region | |||||||
|---|---|---|---|---|---|---|---|
| ① | ○ | × | ○ | × | × | ○ | × |
| ② | ○ | ○ | ○ | × | × | × | × |
| ③ | × | ○ | ○ | × | ○ | × | × |
| ④ | × | × | × | ○ | ○ | ○ | ○ |
The column agrees with the column in all four rows. What makes this check a proof is that the four regions exhaust .
Example 4.5(Checking with concrete sets)
Let , let be the set of even numbers in , and let the set of multiples of in ; that is,
First compute the left-hand side. Since ,
Now the right-hand side. We have and , so picking out the common elements,
The two agree. Reading off the meaning: the numbers that are neither even nor multiples of are not “the primes up to together with and ” but, correctly, “the natural numbers at most divisible by neither nor ”, namely .
Not every operation shares the properties of arithmetic. Set difference is not associative. Taking ,
and these differ. Hence the unparenthesized notation is not permissible. The analogy ” and are associative, so must be too” breaks down here.
5. Predicates and quantifiers
Section titled “5. Predicates and quantifiers”5.1. Predicates
Section titled “5.1. Predicates”Definition 5.1(Predicate)
Fix a set . If for each a proposition is determined, then is called a predicate (or condition) on , and is called the domain of .
"" becomes a predicate on once we fix as the domain: is true, is false, and so on — truth is decided only after a value is substituted for . Note that leaving the domain unstated changes the truth value. “There exists with ” is false with domain (irrationality of the square root of 2(Theorem 7.5)[Techniques of Proof]) and true with domain (existence of √2(Theorem 5.6)[What Is a Number? From the Naturals to the Reals, and Why 1 = 0.999… Is True]).
Definition 5.2(Universal and existential quantifiers)
For a predicate on we define the following two propositions.
- : true if and only if is true for every element of .
- : true if and only if there is at least one for which is true.
We call the universal quantifier and the existential quantifier, and refer to them collectively as quantifiers.
Let us record the values when the domain is empty. If , then is true: were it false, there would have to be some with false, but has no elements. On the other hand is false: before asking whether is true, there is no with at all. This is a restatement of the vacuous truth seen in Proposition 3.6.
5.2. How to form negations
Section titled “5.2. How to form negations”Theorem 5.3(Negation of quantifiers)
Let be a set and a predicate on . Then
Proof(Theorem 5.3)
We prove the first equivalence.
() Suppose is true. Assume for contradiction that the conclusion is false. By Definition 5.2, this says that there is no making true. Then for every the statement is false, that is, is true. By Definition 5.2 this means is true, contradicting the assumption . Hence is true.
() Suppose is true, and pick an element with true. If were true, then since we would get that is true, contradicting the truth of . Hence is false, that is, is true.
The second equivalence follows by applying the first to the predicate . Indeed, the first gives , and since and take the same truth value (applying twice in the table of Definition 2.3 returns the original value), we obtain . Negating both sides and removing the double negation again yields .
Combining this theorem with the last assertion of Proposition 2.4 ( is ) lets us push a negation mechanically inward through a formula of any length. There are only three steps.
- Change a leading into and a leading into , moving the one step inward.
- Replace by , and by (Lemma 4.3).
- Replace by (Proposition 2.4).
flowchart TB S0["¬ ∀ε ∃δ ∀x ( P ⟹ Q )"] --> S1["∃ε ¬ ∃δ ∀x ( P ⟹ Q )"] S1 --> S2["∃ε ∀δ ¬ ∀x ( P ⟹ Q )"] S2 --> S3["∃ε ∀δ ∃x ¬( P ⟹ Q )"] S3 --> S4["∃ε ∀δ ∃x ( P ∧ ¬Q )"]
Example 5.4(Negating the definition of continuity)
A real-valued function is continuous at a point when
holds. We form the negation by the three steps above, using Theorem 5.3 in the first three stages and Proposition 2.4 in the last.
Put into words: there exists some such that, however small one takes , one can find a point lying within distance of whose value nevertheless deviates by at least .
Let us use this. We show that
is not continuous at . Take . Let be arbitrary and choose . Then , and since we have while , so
As was arbitrary, the negation above holds. Hence is not continuous at .
5.3. The order of quantifiers
Section titled “5.3. The order of quantifiers”Remark 5.5(The order must not be interchanged)
When a and an follow one another, their order changes the meaning. With domain :
- is true, because may be chosen after is given; take .
- is false, because must be fixed first, and then choosing makes fail. Using Theorem 5.3, its negation is , and indeed satisfies the condition.
The same phenomenon occurs for the continuity of Example 5.4. In continuity, may be chosen in response to both and the point ; but moving inside to obtain
forbids to depend on . This is the definition of uniform continuity, a stronger condition than continuity at each point. A single difference in the order of symbols produces an entirely different notion.
5.4. Generalization to families of sets
Section titled “5.4. Generalization to families of sets”Corollary 5.6(De Morgan's laws (for families of sets))
Let be a non-empty set and suppose that for each a set is given. Defining
we have
Proof(Corollary 5.6)
We prove the first identity. Take arbitrary. At the second line we use the second half of Theorem 5.3 (the one turning into ).
Since the equivalence holds for every , the two sides are equal by Axiom 3.2. The second identity is obtained by using, at the second line of the same chain, the first half of Theorem 5.3 (the one turning into ).
The case where has two elements is Theorem 4.4. Thus Lemma 4.3, Theorem 4.4 and Corollary 5.6 are three manifestations of a single rule, which fits into one sentence: negation interchanges with , with , and with .
6. Necessary conditions, sufficient conditions, equivalence
Section titled “6. Necessary conditions, sufficient conditions, equivalence”Definition 6.1(Necessary and sufficient conditions)
For propositions and such that is true, we say that
- is a sufficient condition for , and
- is a necessary condition for .
When both and are true, that is when is true, we say that is a necessary and sufficient condition for , and that and are equivalent.
The way to remember this is: the side the arrow leaves is sufficient, the side it enters is necessary. Since asserting alone already yields , the condition is “sufficient”; and since cannot hold if fails (the contrapositive, Proposition 2.4), the condition is “necessary”.
Example 6.2(Numbers whose square is 4)
Consider three conditions on a real number . : ; : ; : .
- is a sufficient condition for , since gives . It is not a necessary one: satisfies but not , so is false.
- is a necessary condition for . This is nothing but a restatement of the truth of , read as: in order for , one must at least have .
- is a necessary and sufficient condition for . If then . Conversely, if then , so or , and in either case .
Note that the sentence ” is a sufficient condition for ” treats the condition as the stronger one. A strong condition (one satisfied by few numbers) is a sufficient condition; a weak condition (one satisfied by many) is a necessary condition. The next proposition makes this intuition exact.
Proposition 6.3(Truth sets and their correspondence with logic)
Let be a set and let , be predicates on . Define the truth set
(taking as the universal set). Then the following hold.
Proof(Proposition 6.3)
(1) By Definition 3.3, means “for every , ”. By the definition of a truth set, is equivalent to ” and is true”, and is equivalent to ” and is true”. Restricting the domain to makes automatic, so the condition coincides with “for every , ”.
(2) Take arbitrary. By definition, says ” is true”, that is ” is true and is true” (Definition 2.3), which is equivalent to and , that is to (Definition 4.1). Since the equivalence holds for every , Axiom 3.2 gives . The claims for and follow by exactly the same procedure, since is the very definition of and that of the complement.
By (1), ” is a sufficient condition for ” is the same as "". In Example 6.2 we have and , so , and the conclusion that is sufficient but not necessary is visible at a glance as an inclusion. The slogan “a sufficient condition is a small set, a necessary condition a large one” refers to exactly this inclusion.
Remark 6.4(The limits of naive set theory)
If, as in Definition 3.1, one supposes that writing down a condition produces a set, the theory collapses. Suppose we form the set
from the condition "". If , then satisfies the condition, so . Conversely, if , then satisfies the condition, so . Either way we get a contradiction (Russell, 1901).
Modern axiomatic set theory (ZFC) abandons the principle that a set may be formed from an arbitrary condition, and permits only carving out a subset of an already existing set by a condition (the axiom schema of separation). This is why comprehension has always been written in the form in this article, with the domain made explicit. The question of what an axiom system does and does not guarantee leads on to Incompleteness theorems (the first incompleteness theorem(Theorem 5.1)[ゲーデルの不完全性定理]). And how far back one must define the meanings of the symbols before an equation such as "" is settled is taken up in What is a number?.
7. Exercises
Section titled “7. Exercises”Exercise 7.1Easy
Let .
(1) Write out and check that the number of its elements agrees with Theorem 3.8.
(2) Decide, with reasons, whether each of the following four assertions is true or false: , , , .
Solution
(1) The elements of are and , two in number. Listing the subsets by their number of elements: with elements, ; with element, and ; with elements, . Hence
which has elements, in agreement with Theorem 3.8.
(2)
- is true, since is listed as an element of .
- is true, since by part (1) of Proposition 3.6 the empty set is a subset of every set.
- is true, since the second element of is .
- is true: the only element of is , and holds, so the condition of Definition 3.3 is met.
All four come out true in this example, but only because of the special circumstance that is both “an element of ” and “the content of a set all of whose elements belong to ”. In general, regard and as unrelated.
Exercise 7.2Standard
For , prove
by element chasing.
Solution
Following Proposition 3.4, we prove two inclusions.
() Let . By Definition 4.1, or .
- Case : from we get and , hence .
- Case : then and . From we get , and from we get . Hence .
In either case lies in the right-hand side, so .
() Let , that is and . We split according to whether .
- Case : then immediately .
- Case : from and it follows that (by the definition of , if is false then is true). Likewise and give . Hence , and so .
In either case lies in the left-hand side, so .
From the two inclusions, Proposition 3.4 gives the equality.
Exercise 7.3Standard
A real sequence converges to a real number when
holds.
(1) Write the negation of this assertion with all quantifiers brought to the front.
(2) Show that the sequence defined by converges to no real number .
Solution
(1) We use Theorem 5.3 three times, then Proposition 2.4 once.
(2) Let be an arbitrary real number and take . Let be arbitrary. Assume, for contradiction, that holds for every with .
Let be an even number at least and an odd number at least (one of is even and the other odd, so both exist). By assumption and . The triangle inequality gives
But and , so , and we arrive at the contradiction .
Hence the assumption fails, and there exists with and . Since was arbitrary, the negation from (1) holds and does not converge to . Since was arbitrary too, this sequence converges to no real number.
Exercise 7.4Hard
For define the symmetric difference by . Show that for ,
Solution
We first prove, as a lemma, that for ,
By Definition 4.1, says ” and ”, while says ” and ”. By the definition of union, says that one of these two holds, that is, that belongs to only or to only, which is the same as “exactly one”.
Next, write for the number of the sets , , to which belongs, and prove the assertion
Applying the lemma to and , the statement says that exactly one of "" and "" holds. We split according to whether .
- Case : the condition becomes , which by the lemma says that and either both hold or both fail. Then the number of , containing is or , hence even, and adding for makes odd. Conversely, if is odd and , the number of , containing is even, so the condition holds.
- Case : the condition becomes , that is, the number of , containing is . The contribution of is , so , which is odd. Conversely, if is odd and , the number of , containing is itself, which is odd and at most , hence , so the condition holds.
The equivalence holds in both cases, which proves the assertion.
Now apply the same argument to . By the lemma applied to and , the statement says that exactly one of "" and "" holds. We split according to whether .
- Case : the condition becomes , so the number of , containing is or , hence even. Adding for makes odd. The converse holds similarly.
- Case : the condition becomes , so the number of , containing is . The contribution of is , so , which is odd. The converse holds similarly.
Hence is odd as well.
Therefore, for every ,
so the two sets are equal by Axiom 3.2.
References
Section titled “References”- Kazuo Matsuzaka, Shugo, Iso Nyumon (in Japanese), Iwanami Shoten, 1968 — Chapter 1, “Sets and maps”. A standard Japanese introduction, careful with proofs of set identities.
- Masahiko Saito, Sugaku no Kiso: Shugo, Su, Iso (in Japanese), University of Tokyo Press, 2002 — Chapter 1. Shows clearly the path from set theory to the construction of the real numbers.
- Shoichi Nakajima, Shugo, Shazo, Ronri: Sugaku no Kihon o Manabu (in Japanese), Kyoritsu Shuppan, 2012 — devotes considerable space to reading and writing formulas and to handling quantifiers.
- Shoji Maehara, Kigo Ronri Nyumon (in Japanese), Nippon Hyoron Sha, 1967 (reissued 2005) — a standard introduction treating propositional and predicate logic formally.
- P. R. Halmos, Naive Set Theory, Van Nostrand, 1960 — Chapters 1 to 5. A short classic bridging naive and axiomatic set theory.
Appendix: A list of frequently used equivalences
Section titled “Appendix: A list of frequently used equivalences”Consult this when a proof stalls. Here , , are propositions and , , are subsets of ; only in the last two rows (negation of quantifiers) is a predicate on a domain . That the two sides always take the same truth value (or, for sets, denote the same set) can be verified by a truth table or by element chasing.
| Name | Logical form | Set form |
|---|---|---|
| Double negation | and | |
| De Morgan | and | |
| De Morgan | and | |
| Distribution | and | |
| Distribution | and | |
| Absorption | and | |
| Unfolding implication | and | and |
| Contraposition | and | and |
| Negation of implication | and | and |
| Negation of a quantifier | and | — |
| Negation of a quantifier | and | — |
Of these, only absorption is not treated in the body, so we record how to check it. If then (the first half of the definition of intersection). Conversely, if then also , so . Hence the two are equal by Proposition 3.4.
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