Combinations

https://www.youtube.com/watch?v=0iMtlus-afo&list=TLPQMjQxMDIwMjBfeWCl0eYdng&index=30 https://en.wikipedia.org/wiki/Pascal%27s_triangle https://en.wikipedia.org/wiki/Binomial_theorem https://en.wikipedia.org/wiki/Binomial_distribution https://rosettacode.org/wiki/Combinations_and_permutations https://en.wikipedia.org/wiki/Combination https://en.wikipedia.org/wiki/Permutation https://rosettacode.org/wiki/Gamma_function https://rosettacode.org/wiki/Evaluate_binomial_coefficients https://en.wikipedia.org/wiki/Twelvefold_way https://en.wikipedia.org/wiki/Multiset https://en.wikipedia.org/wiki/Partition_of_a_set https://en.wikipedia.org/wiki/Partition_(number_theory)

Combinatorics studies the problems concerning counting and ordering, such as partitioning and enumerations. The number of ways to select kk objects from the set containing nn objects is denoted and calculated by:

C(n,k)= nCk=(nk)=(nnk)=n!k!(nk)!\displaystyle{ C(n,k) = \ _nC_k = {n \choose k} = {n \choose n - k} = \frac {n!} {k!(n - k)!} }

The expression (nk)n\choose k is read "n choose k".

This formula shows that the number of ways to select 3 elements from the 10-element set is the same as the number of ways to select 7:

(103)=(107)=10!3!7!=10!7!3!\displaystyle{ {10 \choose 3} = {10 \choose 7} = \frac{10!}{3!7!} = \frac{10!}{7!3!} }

Each combination C(n,r)C(n,r) has a certain frequency and frequency ratio and all frequency ratios sum up to 1.

Combinations, Pascal's triangle, Powers of 2, Powerset, Binomial coefficient

In combinations, the order in which we select objects is irrelevant. We're only interested in the subsets that we can form out of a given set and/or number of subsets.

If a given set A contains 5 elements, A = {a,b,c,d,e}, we might as well imagine the set A as an opaque bag that contains 5 marbles (labelled with letters a-e). Then, we might be interested, for example, in finding out the number of ways we can pick 3 distinct elements from A (with the order in which the individual elements are picked is immaterial).

These types of problems have their own form of expression, (nk)n\choose k (read "n choose k"), with n being the total number of elements and k the number of elements we'd like to select.

Partitions

https://en.wikipedia.org/wiki/Partition_(number_theory) https://artofproblemsolving.com/wiki/index.php/Partition_(combinatorics)

In combinatorics, C(n,r), since r must be 0 <= r <= n, we can consider all the cases of C(n,r[i]) where i iterates from 0 to n.

For example, C(3,r) can be partitioned into 4 partitions: C(3,0), C(3,1), C(3,2), C(3,3). Each partition has a certain frequency.

Adding these frequencies together we get the total number of partitions possible for a set of n elements (with variable r i.e. variable partition size): C(3,0)=1 + C(3,1)=3 + C(3,2)=3 + C(3,3)=1 => 8

In set theory, powerset contains all possible subsets of some particular set. So the number 8 obtained above, is the number of elements in the powerset (of a set with 3 elements), 2n=82^n = 8, i.e. if a set has 3 elements, then the cardinality of its powerset is 8.

A particular partition frequency can be divided by the number of all possible partitions to get the ratio of those combos accounted for by that particular partition. E.g. C(3,1)=3, so its frequency ratio is 3/8. Adding all freq. ratios amounts to 1. E.g. 1/8 + 3/8 + 3/8 + 1+8 = 1

Examples

List all 2-element partitions of a 4-element set

The number of 2-element partitions: C(4,2) = 4!/2!2! = 12/2 = 6

Let set A={a,b,c,d}, then there are 6 two-element subsets of P(A): ab, ac, ad, bc, bd, cd (incorrect but convenient notation)

How many ways to choose 2 out of 4

n=4,  r=2n=4,\ \ r=2

n!r!(nr)!=4!2!(42)!=4!2!2!=43!2!!=6\frac{n!}{r!(n-r)!} = \frac{4!}{2!(4-2)!} = \frac{4!}{2!·2!} = \frac{4·3·\not 2!}{2!·\not 2!} = 6

How may distinct pairs can be made with 4 elements

(nk)=(42)=4!2!=432!2!=6{n \choose k} = {4 \choose 2} = \frac{4!}{2!} = \frac{4·3·2!}{2!} = 6

Check: X={a,b,c,d} n=4 6 pairs: ab, ac, ad, bc, bd, cd

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