Probability in R. Discrete Random Variables

Probability in R is a course that links mathematical theory with programming applications. Discrete Random Variables series gives an overview of the most important discrete probability distributions together with methods of generating them in R. Fundamental functionality of R language is introduced including logical conditions, loops, and descriptive statistics. Viewers are acquainted with basic knowledge of numerical analysis.

The course is designed for students of probability and statistics who would like to enrich their learning experience with statistical programming. While basic knowledge of probability and calculus is a useful prerequisite it is not essential. The suggested method of using the course is by repeating the reasoning and replicating the R code. Therefore students need to download and use R in the course.

The course consists of twelve short lectures totaling two hours of video materials. Four major topics are covered: Bernoulli distribution (2 lectures), binomial distribution (3 lectures), geometric distribution (3 lectures), and Borel-Cantelli lemma (4 lectures). Eight lectures are presented in a form of writing R code. The remaining four lectures focus solely on a theory of probability.

How is Infermath different from other education channels? It equips students with tools and skills to use the acquired knowledge in practice. It aims to show that learning mathematics is not only useful but also fun and inspiring. It emphasizes equal chances in education and promotes an open source approach.