maths.free › Probability Theory › Applying Probability to Combinatorics › A First Taste of Ramsey Theory

A First Taste of Ramsey Theory

Bob likes to think of himself as a wild and crazy guy, totally unpredictable. Most guys do. But Alice says that Bob can't change his basic nature, which is excruciatingly boring.

A First Taste of Ramsey Theory

Bob likes to think of himself as a wild and crazy guy, totally unpredictable. Most guys do. But Alice says that Bob can't change his basic nature, which is excruciatingly boring. Carlos remarks that perhaps we shouldn't be so hard on Bob, because under certain circumstances, we can all be forced to be dull and repetitive.

Recall that when \(n\) is a positive integer, we let \([n]=\{1,2,\dots,n\}\). In this chapter, when \(X\) is a set and \(k\) is a non-negative integer with \(k\le |X|\), we borrow from our in-line notation for binomial coefficients and let \(C(X,k)\)\(C(X,k)\)family of all \(k\)-element subsets of \(X\) denote the family of all \(k\)-element subsets of \(X\). So \(|C([n],k)|=C(n,k)\) whenever \(0\le k\le n\).

Recall that the asserts that if \(n+1\) pigeons are placed in \(n\) holes, then there must be some hole into which two or more pigeons have been placed. More formally, if \(n\) and \(k\) are positive integers, \(t>n(k-1)\) and \(f:[t]\longrightarrow[n]\) is any function, then there is a \(k\)-element subset \(H\subseteq [t]\) and an element \(j\in[n]\) so that \(f(i)=j\) for every \(i\in H\).

We now embark on a study of an elegant extension of this basic result, one that continues to fascinate and challenge.

Returning to the discussion at the start of this section, you might say that an induced subgraph \(H\) of a graph \(G\) is boring if it is either a complete subgraph or an independent set. In either case, exactly every pair of vertices in \(H\) behaves in exactly the same boring way. So is boredom inevitable? The answer is yesat least in a relative sense. As a starter, let's show that any graph on six (or more) vertices has a boring subgraph of size three.

Next, here is the statement that generalizes this result.

Condensed: the full section is in Keller & Trotter, Applied Combinatorics.

Nå har du Ingen kalkulator setter opp denne, men brikkene kan brukes. Prøv en nedenfor eller skriv inn din egen.

Fortsett ditt eget arbeid

En gratis konto legger til notater om hver leksjon, en oversikt over hva du har fullført, problemene du har løst på ett sted og en lærer du kan spørre om. Matematikkene er åpne for alle, signerte på eller ikke.

Registrer Logg inn

Symboler som brukes her

Trykk på et symbol for den fulle definisjonen, et bilde og hva hver bokstav i det betyr.

Spørsmål folk stiller

What is the difference between probability and statistics?

Probability goes from a known model to what the data should look like; statistics goes from data back to the model. Probability theory is the deductive half.

What does the law of large numbers promise?

That the average of many independent samples converges to the expected value. It says nothing about any single trial.

Deler av denne siden er tilpasset fra Keller & Trotter, Applied Combinatorics (CC BY-SA 4.0). Kondensert og re-forklaret her, feil er vår.

Mer i Probability Theory