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Introduction to Probability 001

Probability Models And Axioms

Lecture 01.1 Youtube

Lecture 01.2 Youtube

Sample Space

  • Sample space is a list (set) of possible outcomes, \(\Omega\)
  • Event: a subset of the sample space. Probability is assigned to events.

Probability Axioms

Lecture 01.4 Youtube

  • Nonnegativity: \(P(A) \ge 0\)
  • Normalization: \(P(\Omega) = 1\)
  • (Finite) additivity: (to be strengthened later)

If \(A \cap B = \varnothing\), then \(P(A \cup B) = P(A) + P(B)\)

\(A \cap B\) read as \(A\) intersects \(B\), \(A \cup B\) read as \(A\) unions \(B\)

Lecture 01.5 Youtube

Lecture 01.6 Youtube

Lecture 01.7 Youtube

Lecture 01.8 Youtube

Lecture 01.9 Youtube

  • Countable Additivity Axiom:

If \(A_1, A_2, A_3, \dots\) is an infinite sequence of disjoint events, then \(P(A_1 \cup A_2 \cup A_3 \cup \cdots) = P(A_1) + P(A_2) + P(A_3) + \dots\)

Lecture 01.10 Youtube

Mathematical Background

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