
This short, self-contained course gives you the basics on counting necessary to be successful in probability, stats, genetics, GMAT, GRE, etc. The multiplication principle, additional rule, permutations, combinations, counting strategies, binomial coefficients, multinomial coefficients, inclusion & exclusion, and derangements are covered. In a follow up course, we will cover more involved topics such as generating functions and Polya's counting theory. Abbreviations for applicability to different tests: DAT, GRE, GMAT, MSG (Math Subject GRE), OAT (O), ISSE (I).
Apply the counting principle, i.e., the multiplication rule, to multiply options at each stage, as shown by choosing hats, shirts, and shoes to form outfits.
Explain distinguishable versus indistinguishable objects with examples, showing how the counting principle depends on whether items can be told apart or look identical.
Explore permutations with no replacement and where order matters, using the counting principle to assign president, vice president, and treasurer from ten distinguishable people, and derive n!/(n-k)!.
Learn how to count arrangements with repeats by applying permutations and factorials, dividing by repeated-letter factorials to correct overcount, introducing the multinomial principle.
Here is a quick bonus problem taken from a class lecture John gave.
In this bonus lesson, we will apply our knowledge of combinatorics to probability. For the problem we look at, it is enough to know that the probability can be computed by diving the number of ways of getting "what we want" by the "total number of possibilities" [WANT/TOTAL]. Here, we take for granted that each possibility is equally likely to occur.
A bonus lecture showing two interesting ways of picking 3 nonconsecutive numbers from the numbers 1-10!
Learn the stars and bars approach to multichoose by counting distributions of indistinguishable balls into distinguishable urns, using dividers as bars and multinomial reasoning.
Explore multichoose and stars and bars by counting ways to place indistinguishable balls into distinguishable urns using the (n+r-1 choose r-1) formula, and relate it to group selection with replacement.
Explore the pigeonhole principle: if P pigeons exceed H holes, some hole contains at least two pigeons, and more generally, if P > H·M, some hole has at least M+1.
Explore how the pigeonhole principle in combinatorics solves a six-person party problem, showing that among any six people at least three form a mutual friend or enemy group.
Explore how the pigeonhole principle guarantees a line segment among five lattice points has a midpoint that is also a lattice point, by classifying points by parity of coordinates.
Explore a binomial identity for the principle of inclusion-exclusion, showing the sum k=0 to n of (-1)^k n choose k equals zero, with algebraic and combinatorial proofs.
Master the inclusion-exclusion principle for counting unions, from A to B to C, subtracting pairwise intersections and adding back triple intersections, with the negative form and universe complements.
Apply the counting pattern of adding single set sizes, subtracting pairwise intersections, adding back triples, and extending to n sets to count unions with the binomial identity.
Apply the inclusion–exclusion principle to a multichoose problem: count ways to pick 30 balls from four colors by complementing with binomial coefficients, yielding 286.
Count derangements in the party hat problem using inclusion-exclusion and factorials. Explore the probability of everyone missing their own hat and its convergence to e^{-1} as n grows.
Explore a slower, teaching-friendly proof of the principle of inclusion and exclusion, counting with unions and intersections and using parity, then generalize to a universe-based pie formulation.
An application to Fibonacci numbers!
John does a quick video on Burnside's Lemma (an advanced topic for this course). Let us know if you want a more extensive explanation!
Learn the multiplication rule, permutations, combinations, n choose r with repetition, multinomial, the principle of inclusion and exclusion, partitions, and derangements. John will take you through the ideas and techniques you need to get a firm handle on counting concepts and applications. This course is perfect for people wanting to learn counting strategies for tests such as the GRE, DAT, and GMAT, for anyone interested in Data Science, for anyone studying combinatorics , probability, or statistics, and for those just interested in interesting enumeration problems. John mentions some extra applications that require some knowledge of numbers such as "e," but these applications can easily be skipped with no loss of continuity.
Combinatorics is a growing field utilized in data science, computer science, statistics, probability, engineering, physics, business management, and everyday life. This course is a great introduction with some specialized topics. It is best for someone getting started. If you are more experienced, this course is not for you unless you want to revisit the core concepts. Please see the list of topics.
*Although this course covers only the topics listed, the material can be challenging and demand time to fully absorb!
**This is paced as "Beginner" for a US College Course. But, on UDEMY the course rated 5.0 until a student rated the it a 1.0 due to the difficulty. A few other students commented that they loved the course but that it was set at a difficulty level greater than "Beginner" with respect to many UDEMY courses. To be consistent with the platform, the class has been adjusted to an "Intermediate" level course. However, if you are taking a university course in the US on combinatorics, this course would be the equivalent of the first part of a combinatorics class.