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Understanding Probability: Sample Spaces, Events, Measures, and Random Variables, Study notes of Probability and Statistics

An in-depth exploration of probability theory, covering topics such as sample spaces, events, probability measures, and random variables. Learn about concepts like disjoint events, conditional probability, independence, discrete and continuous random variables, and more.

Typology: Study notes

2019/2020

Uploaded on 01/02/2020

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Review of Probability Theory
Zahra Koochak and Jeremy Irvin
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Download Understanding Probability: Sample Spaces, Events, Measures, and Random Variables and more Study notes Probability and Statistics in PDF only on Docsity!

Review of Probability Theory

Zahra Koochak and Jeremy Irvin

Elements of Probability

Elements of Probability

Sample Space Ω {HH, HT , TH, TT }

Elements of Probability

Sample Space Ω {HH, HT , TH, TT } Event A ⊆ Ω

Elements of Probability

Sample Space Ω {HH, HT , TH, TT } Event A ⊆ Ω {HH, HT }, Ω

Elements of Probability

Sample Space Ω {HH, HT , TH, TT } Event A ⊆ Ω {HH, HT }, Ω Event Space F

Elements of Probability

Sample Space Ω {HH, HT , TH, TT } Event A ⊆ Ω {HH, HT }, Ω Event Space F Probability Measure P : F → R P(A) ≥ 0 ∀A ∈ F

Elements of Probability

Sample Space Ω {HH, HT , TH, TT } Event A ⊆ Ω {HH, HT }, Ω Event Space F Probability Measure P : F → R P(A) ≥ 0 ∀A ∈ F P(Ω) = 1

Conditional Probability and Independence

Conditional Probability and Independence

Let B be any event such that P(B) 6 = 0.

Conditional Probability and Independence

Let B be any event such that P(B) 6 = 0. P(A|B) := P P(A(∩BB)) A ⊥ B if and only if P(A ∩ B) = P(A)P(B)

Conditional Probability and Independence

Let B be any event such that P(B) 6 = 0. P(A|B) := P P(A(∩BB)) A ⊥ B if and only if P(A ∩ B) = P(A)P(B) A ⊥ B if and only if P(A|B) = P(A∩B) P(B) =^ P(A)P(B) P(B) =^ P(A)

Random Variables (RV)

ω 0 = HHHTHTTHTT

Random Variables (RV)

ω 0 = HHHTHTTHTT A RV is X : Ω → R