# Course review: Alison’s Probability and Combinatorics Course

I have been endeavouring to upgrade my skill in data science by studying topics that I did not study when I was in higher education. I therefore took a stab at studying probability and decided to take an Alison course entitled Probability and Combinatorics. I was under time constraints, so I did not have the opportunity to thoroughly study the topic as much as I would like, but I nevertheless completed the course.

I have decided to review the course and, although Python code was not part of the course, I decided to insert some code in the review as well. The great thing about Python is the fact that it enables people to calculate probability even if they are not very adept at calculating it by hand.

Module 1: Permutations and fundamental counting principle

Permutations

A permutation is an arrangement of objects in a specific order. For example, the set {1,2,3} has 3! = 6 possible permutations: (1,2,3), (1,3,2), (2,1,3), (2,3,1), (3,1,2), and (3,2,1). In general, if a set has n elements, there are n! possible permutations of those elements.

The formula for permutation of n objects taken n at a time is written as nPn and is calculated using the following formula: