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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.

Manje Akukho kalkuli yokuxazulula le nto, kodwa amaphuzu ayo anga kalkuli. Zama enye ngezansi, noma ubhale yakho.

Uqeqesho (1)

Zama ngayinye yazo kuphepha kuqala. Bonisa impendulo ukuze ubheke; okunye okuqinisekisiwe kungavuliwa ku-solver ngayinye yesigaba.

  1. How many terms are there in the sum of if \(m=10\)? Explain your reasoning.

Qhubeka usebenza

I-akhawunti emahhala ifaka iziphawulo kulesifundo ngasinye, irekhodi lokuthi yini oqedile, izinkinga zakho ezixazululiwe endaweni eyodwa, nodokotela owaziyo ongabuza mayelana nalekhasi. I-matematics ivulekile kubo bonke, noma ngabe babhalise noma cha.

Bhala Ngena

Amaphawu asetshenziswa lapha

Chofoza noma yiluphi uphawu lwesibonakaliso ukuze uthole ukuchaza okuphelele, isithombe, kanye nokuthi iyiphi inhlamvu ekhona ekhuluma ngaso.

Imibuzo abantu bebuza

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.

Amangxenye wale khasi aguqulwe kusuka Keller & Trotter, Applied Combinatorics (CC BY-SA 4.0). I-condensed futhi iphinde icaciswe lapha; amaphutha awusizo.

Okuningi Combinatorics & Graph Theory