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Foundations of mathematics asks what our objects mean, what we assume about them, and why an argument establishes its conclusion. Set theory gives a common language for collections and functions; mathematical logic makes the structure of statements and deductions precise. A mathematical definition fixes a meaning, an axiom supplies an assumption, and a mathematical proof explains what follows. Separating these roles makes results reusable: once the group axioms are enough for a conclusion, that conclusion applies to every group, regardless of how its members are represented.

The assumptions can change the answer to a familiar calculation. Over the real numbers, $x^2=x$ factors as $x(x-1)=0$, so $x$ is zero or one. The same reasoning holds in any integral domain, because a product can be zero only when a factor is zero. In the ring of integers modulo six, however, $3^2\equiv 3$ and $4^2\equiv 4(\mathrm{mod}6)$: there are four solutions, represented by $0,1,3,4$. The extra solutions are idempotents, and the failed step involves zero divisors. Writing the domain is part of explaining the answer.

This precision also reveals surprising possibilities. A two-dimensional grid of natural numbers is a countable set, while all infinite binary sequences form an uncountable set. The Cantor pairing function supplies a complete enumeration of the first; Cantor's diagonal argument defeats every proposed enumeration of the second. Both arguments are short, yet distinguish two sizes of infinity. The subject's appeal is this ability to turn a vague question into one whose assumptions, construction, and limits can all be inspected.

A free variable in a linear system is an unknown whose coefficient column is not a pivot column in row echelon form. When the linear system is consistent, it can be assigned any value in the field; the pivot unknowns are then determined by those choices. This use of “free” differs from a free variable in mathematical logic.

Author of An Investigation of the Laws of Thought by George Boole, applying symbolic operations to mathematical logic.

Mathematical logic studies formal languages, formal proofs, model theory, computability theory, and the foundations of mathematics. It makes the rules of reasoning explicit enough that reasoning itself becomes an object of mathematics. Proof theory studies deductions; model theory studies interpretations in which statements hold.

Three questions organize the subject: is an expression a well-formed first-order formula, is it true in a specified first-order structure, and does it have a formal proof from specified axioms? These questions are distinct. For example, $\exists n(n+n=1)$ is a first-order sentence in an appropriate first-order language; it is false in the natural numbers but true in the rational numbers, with $n=1/2$.

The beauty of mathematical logic is that the same logical connectives and rules of universal quantification and existential quantification organize arguments across mathematics. Classical propositional logic uses two truth values; Intuitionistic propositional logic interprets logical implication through constructions on proofs, without unrestricted law of excluded middle. This proof-based framework is developed in Frank Pfenning, Natural Deduction, sections 1–3.

This University of Oxford Part B paper is cross-listed for Mathematics, Mathematics and Computer Science, Mathematics and Philosophy, and Mathematics and Statistics. Section A concerns mathematical logic and section B concerns set theory. ^[ref] The archive contains a complete editable five-page transcription. Bounded official-source searches found no advertised answers to this exact paper. All 29 source leaves and the attached unnumbered tasks are covered below. In Q7(v), the convergence condition is retained exactly as printed, without adding absolute-value bars.

This University of Oxford Part B paper is cross-listed for Mathematics, Mathematics and Computer Science, Mathematics and Philosophy, and Mathematics and Statistics. It contains mathematical logic in section A and set theory in section B. ^[ref] The archive contains the full editable five-page transcription. Bounded official-source searches found no advertised answers for this exact 2008 paper. All source leaves are solved below, including all five optional arguments in A1(e) and the unnumbered preliminary tasks in B5, B6 and B7.

Ramsey theory studies configurations that every finite coloring of a sufficiently large structure must contain. Its striking message is that some order is unavoidable even when no organized construction was used. A basic example is the Ramsey number for triangles: color every edge of a complete graph on six vertices red or blue, in any way, and some triangle in a graph has all three edges the same color. Five vertices do not suffice.

The objects receiving colors matter. In the Ramsey number for triangles, colors belong to edges, which represent all unordered pairs of distinct vertices; the vertices themselves have no colors. In the finite Ramsey theorem, colors can instead belong to all $r$-element subsets of a finite set. A monochromatic set or homogeneous set for a colouring expresses agreement among the appropriate colored objects.

Why is this useful? Ramsey theory provides existence guarantees in combinatorics that survive every possible assignment of a fixed finite number of colors. The Ramsey theorem turns this into a structural dichotomy: every sufficiently large graph contains a large clique or a large independent set. In arithmetic, the Van der Waerden theorem guarantees monochromatic arithmetic progressions. The beauty is the universal quantifier: an adversary can choose every color and still cannot prevent the promised configuration.

These guarantees concern precisely specified configurations under stated hypotheses. They do not justify selecting arbitrary patterns in empirical data after seeing the data, or attributing statistical significance to a selected pattern. A mathematical guarantee of some monochromatic configuration alone says nothing about the empirical meaning of that configuration.

The subject's name comes from F. P. Ramsey's ^[ref]. The ^[ref] records receipt on 28 November 1928 and presentation on 13 December 1928. Ramsey introduced the Ramsey theorem for r-sets and finite Ramsey theorem as tools for a problem in mathematical logic, while recognizing their independent interest in combinatorics. He also distinguished proving that a finite threshold exists from finding its smallest value, the quantitative question captured by a Ramsey number.