Probability Theory
INTERMEDIATE
#python
Author: Diana Sadyrova
Course description
We meet probability every day but do not even recognize it! This course will introduce you to the basic terms. You will combine math and programming learning with real-life examples.
Complete all chapters to get certificate
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Learn Basic Rules
It's time to dive deeper into the probability theory. Here we will learn basic formulas. The main idea of the section is to help us to understand the term probability using real-life examples.
Random Variable
Bernoulli Trial 1/2
Bernoulli Trial 2/2
Binomial Probability 1/2
Binomial probability
Probabilities of Several Events
Here, we will get acquainted with the rules in probability theory. This section will be more complicated than the previous one. It will be attractive because we are going to work with the real challenges. But it should be noted that we learn some formulas.
Add Probabilities
Calculate Connected Probabilities
Challenge
Multiply probabilities
Dependent probabilities
Law of Total Probability
Bayes Theorem
Challenge
Conducting Fascinating Experiments
Doing experiments is always funny, but here we will combine exciting tasks with programming learning. In this section, we will work with the binom object to conduct experiments in Python.
The First Experiment
The Second Experiment
The Third Experiment
Combine Your Knowledge
Discrete Distributions
Distribution is a key to probability learning, but don't be petrified by this term. This section provides you with real-life explanations and relevant formulas.
Discrete Uniform Distribution
Calculate Fascinating Probability
Bernoulli Distribution
Binomial Distribution
Challenge
Poisson Distribution
Challenge
Normal Distribution
The normal distribution is the most commonly used one. Here we will work with the distribution with the help of real-life challenges.
Normal Distribution
Challenge 1
Сhallenge 2