maths.free › Combinatorics & Graph Theory › Inclusion-Exclusion › The Inclusion-Exclusion Formula
The Inclusion-Exclusion Formula
Now that we have an understanding of what we mean by a property, let's see how we can use this concept to generalize the process we used in the first two examples of the previous section.
The Inclusion-Exclusion Formula
Now that we have an understanding of what we mean by a property, let's see how we can use this concept to generalize the process we used in the first two examples of the previous section.
Let \(X\) be a set and let \(\mathcal{P}=\{P_1,P_2,\dots,P_m\}\) be a family of properties. Then for each subset \(S\subseteq [m]\), let \(N(S)\) denote the number of elements of \(X\) which satisfy property \(P_i\) for all \(i\in S\). Note that if \(S=\emptyset\), then \(N(S)=|X|\), as every element of \(X\) satisfies every property in \(S\) (which contains no actual properties).
Returning for a moment to with \(P_1\) being is a computer science major and \(P_2\) being is male, we note that \(N(\{1\})=47\), since there are \(47\) computer science majors in the class. Also, \(N(\{2\})=51\) since \(51\) of the students are male. Finally, \(N(\{1,2\})=45\) since there are \(45\) male computer science majors in the class.
In the examples of the previous section, we subtracted off \(N(S)\) for the sets \(S\) of size \(1\) and then added back \(N(S)\) for the set of properties of size \(2\), since we'd subtracted the number of things with both properties (male computer science majors or solutions with both \(x_3>7\) and \(x_4'>8\)) twice. Symbolically, we determined that the number of objects satisfying none of the properties was \[\begin{aligned}\end{aligned}\]
Suppose that we had three properties \(P_1,P_2\), and \(P_3\). How would we count the number of objects satisfying none of the properties? As before, we start by subtracting for each of \(P_1\), \(P_2\), and \(P_3\). Now we have removed the objects satisfying both \(P_1\) and \(P_2\) twice, so we must add back \(N(\{1,2\})\). similarly, we must do this for the objects satisfying both \(P_2\) and \(P_3\) and both \(P_1\) and \(P_3\). Now let's think about the objects satisfying all three properties. They're counted in \(N(\emptyset)\), eliminated three times by the \(N(\{i\})\) terms, and added back three times by the \(N(\{i,j\})\) terms. Thus, they're still being counted! Thus, we must yet subtract \(N(\{1,2,3\})\) to get the desired number: \[\begin{aligned}\end{aligned}\] We can generalize this as the following theorem:
Condensed: the full section is in Keller & Trotter, Applied Combinatorics.
Indi sen Hiç bir hasapçy buny çözmez, emma onuň bölekleri hasaplanmak üçindir. Aşakda birini synla ýa-da özüňi ýaz.
Tälim (1)
Her birini kagyzda synlap gör. Çözgüni barlap görmek üçin aç; barlap görlenler her bir ädim üçin çözgüççide açylyp bilner.
-
How many terms are there in the sum of if \(m=10\)? Explain your reasoning.
Şu ýerde ulanylan simwollar
Eň täze düşündirme, surat, we her harpyň manysy üçin her bir simwoly basyň.
Adamlar soraýan soraglar
Permutation or combination?
Ask whether order matters. A lock code is a permutation (order matters); a hand of cards is a combination (it does not).
What is a graph in this sense?
Dots (vertices) joined by lines (edges), not a plot. Road maps, social networks and molecules are graphs; questions like "is there a route" and "how few colours" are graph theory.
Bu sahypanyň käbir bölegi şundan alyndy Keller & Trotter, Applied Combinatorics (CC BY-SA 4.0). Bu ýerde gysgaldylan we tekrar beýan edilen; hatalar biziňkidir.
_Ýaşa Combinatorics & Graph Theory
The counting principlesPigeonhole principle and inclusion, exclusionBinomial coefficients and Pascal's triangleRecurrences and generating functionsGraphs: vertices, edges, degreesPaths, cycles, trees, Euler and HamiltonColouring and planar graphs