Introduction
In this first lecture, we will study the Bernoulli and Binomial distributions. The Bernoulli distribution is especially important because it serves as the building block for many other probability distributions.
This lecture is divided into two main sections:
Section 1: We will introduce the Bernoulli distribution, explain its key characteristics (mean, variance, and probability mass function), and work through some examples using the open-source software R.
Section 2: We will study the Binomial distribution, explore its main properties, and perform both manual calculations and visualizations in R.
The PDF attachment provides the lecture notes, worked examples, and R code for reference.
During our exercise sessions (TD), we will practice additional examples together, solve applied problems, and strengthen our understanding of both distributions.
Learning Outcomes
By the end of this lecture, you should be able to:
Define and explain the Bernoulli and Binomial distributions.
Calculate their expected values and variances.
Use R to compute probabilities and visualize the distributions.
Apply these concepts to practical problems in statistics.
- Teacher: mouhcene Hamrit