Data Science and Machine Learning (Theory and Projects) A to Z - Probability Model: Probability Axioms

The video tutorial covers the three main axioms of probability: non-negativity, additivity, and the probability of the sample space being one. It explains how these axioms form the foundation for understanding probability, using examples like rolling a fair die to illustrate concepts. The tutorial also discusses the probability range between 0 and 1, and derives properties such as the probability of an empty set being zero.

What are the three main axioms of probability?

Explain the first axiom of probability.

What does the axiom of additivity state?

How can the axiom of additivity be extended to several events?

How does the concept of mutually exclusive events relate to probability?

What is the probability of the sample space?

Describe how to calculate the probability of an event using the axioms.

How can one derive more properties from the axioms of probability?

What is the significance of the empty set in probability?

What is the relationship between the sample space and the outcomes of an experiment?