Derangement

\(\{b,c,a\}\) \(\{c,a,b\}\)

Q: A large number of drunk guests arrive at a hotel where they have booked specific rooms. A careless receptionists hands over keys at random. What is the probability that at least one guest ends up in a room she booked?A: A useful concept to understand is that of. A derangement is the number of ways a set can be permuted such that none of the elements are in their respective positions. For example if \(\{a,b,c\}\) is a set, then the derangements of the set areThe above two are the only derangements of the set. The number of possible derangements of a set is usually specified as \(!n\) (note, the exclamation is before the \(n\)). There exists an expansion of \(!n\) which is$$!n = n! \sum_{k=0}^{n} \frac{(-1)^k}{k!}$$Coming back to the probability question at hand, the number of ways by which all guests land up in different rooms from the ones they have booked is simply the number of derangements for the group. The overall number of permutations possible is \(n!\). So the sought probability is$$P(\text{at least one guest in own room}) = 1 - P(\text{no guest in own room})$$which simplifies to$$P(\text{at least one guest in own room}) =1 - \frac{!n}{n!}$$There is an interesting observation to be made here. For large \(n\), the ratio of \(\frac{!n}{n!}\) converges to \(\frac{1}{e}\). i.e.$$\lim_{n \rightarrow \infty} \frac{!n}{n!} = \frac{1}{e}$$So for a large number of guests the sought probability is$$P(\text{at least one guest in own room}) = 1 - \frac{1}{e}$$If you are looking to buy some books in probability here are some of the best books to learn the art of ProbabilityThis book is a great compilation that covers quite a bit of puzzles. What I like about these puzzles are that they are all tractable and don't require too much advanced mathematics to solve.This is a book on algorithms, some of them are probabilistic. But the book is a must have for students, job candidates even full time engineers & data scientistsOverall an excellent book to learn probability, well recommended for undergrads and graduate studentsThis is a two volume book and the first volume is what will likely interest a beginner because it covers discrete probability. The book tends to treat probability as a theory on its ownA good book for graduate level classes: has some practice problems in them which is a good thing. But that doesn't make this book any less of buy for the beginner.A good book to own. Does not require prior knowledge of other areas, but the book is a bit low on worked out examples.An excellent resource (students, engineers and even entrepreneurs) if you are looking for some code that you can take and implement directly on the jobThis is a great book to own. The second half of the book may require some knowledge of calculus. It appears to be the right mix for someone who wants to learn but doesn't want to be scared with the "lemmas"This one is a must have if you want to learn machine learning. The book is beautifully written and ideal for the engineer/student who doesn't want to get too much into the details of a machine learned approach but wants a working knowledge of it. There are some great examples and test data in the text book too.This is a good book if you are new to statistics & probability while simultaneously getting started with a programming language. The book supports R and is written in a casual humorous way making it an easy read. Great for beginners. Some of the data on the companion website could be missing.Covered in this book are the central limit theorem and other graduate topics in probability. You will need to brush up on some mathematics before you dive in but most of that can be done onlineThis book has been yellow-flagged with some issues: including sequencing of content that could be an issue. But otherwise its good