3.1 Terminology A and B are events \(P(S) = 1\) where \(S\) is the sample space \(0 ≤ P(A) ≤ 1\) \(P(A | B)=\frac{P(A \cap B)}{P(B)}\) 3.2 Independent and Mutually Exclusive Events \(\text {If } A \te...3.1 Terminology A and B are events \(P(S) = 1\) where \(S\) is the sample space \(0 ≤ P(A) ≤ 1\) \(P(A | B)=\frac{P(A \cap B)}{P(B)}\) 3.2 Independent and Mutually Exclusive Events \(\text {If } A \text { and } B \text { are independent, } P(A \cap B)=P(A) P(B), P(A | B)=P(A) \text { and } P(B | A)=P(B)\) \(\text {If } A \text { and } B \text { are mutually exclusive, } P(A \cup B)=P(A)+P(B) \text { and } P(A \cap B)=0\) 3.3 Two Basic Rules of Probability The multiplication rule: \(P(A \cap B) …
3.1 Terminology A and B are events \(P(S) = 1\) where \(S\) is the sample space \(0 ≤ P(A) ≤ 1\) \(P(A | B)=\frac{P(A \cap B)}{P(B)}\) 3.2 Independent and Mutually Exclusive Events \(\text {If } A \te...3.1 Terminology A and B are events \(P(S) = 1\) where \(S\) is the sample space \(0 ≤ P(A) ≤ 1\) \(P(A | B)=\frac{P(A \cap B)}{P(B)}\) 3.2 Independent and Mutually Exclusive Events \(\text {If } A \text { and } B \text { are independent, } P(A \cap B)=P(A) P(B), P(A | B)=P(A) \text { and } P(B | A)=P(B)\) \(\text {If } A \text { and } B \text { are mutually exclusive, } P(A \cup B)=P(A)+P(B) \text { and } P(A \cap B)=0\) 3.3 Two Basic Rules of Probability The multiplication rule: \(P(A \cap B) …
