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Dept. Computer Science, Korea Univ. Intelligent Information System Lab. 1 In-Jeong Chung chung@korea.ac.kr Intelligent Information System lab. Department of Computer Science Korea University Probability & Statistics #2
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Dept. Computer Science, Korea Univ. Intelligent Information System Lab. 1.4 Independent Events Def) A, B, C are mutually independent iff ■1) A, B, C are pairwise independent i.e. P(A ∩ B) = P(A) P(B), P(A ∩ C) = P(A) P(C), P(B ∩ C) = P(B) P(C), ■2) P(A ∩ B ∩ C) = P(A) P(B) P(C) ■e.g. ex. 1.4.4 : not mutually independent, but pairwise independent 2
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Dept. Computer Science, Korea Univ. Intelligent Information System Lab. 1.4 Independent Events ■e.g. (p.30 ex 1. 4. 5) Event A i : component C i fails (i = 1, 2, 3) Probability that system would work correctly = probability that system does not fail = 3 C1C1 C2C2 C3C3
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Dept. Computer Science, Korea Univ. Intelligent Information System Lab. 1.4 Independent Events ■e.g. (p.31 ex 1. 4. 9) 5 consecutive days “instant winner” lottery ticket Probability of winning = 1/5 on ∀ day Independent trials Generally, probability of 2 winning tickets & 3 losing tickets 4
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Dept. Computer Science, Korea Univ. Intelligent Information System Lab. 1.5 Bayes’s Theorem Thomas Bayes (1761) Conditional probability ■Motivating e.g. traffic accident 40% of traffic accident : speed ↑event(E) 30% of traffic accident : C 2 H 5 OHevent(A) If C 2 H 5 OH is involved,60% of speed ↑ o.w10% of speed ↑ traffic accident involves speed ↑ ■Probability that C 2 H 5 OH is involved 5
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Dept. Computer Science, Korea Univ. Intelligent Information System Lab. 1.5 Bayes’s Theorem 6 i.e. If speed ↑ was involved in an traffic accident, 72% chance of C 2 H 5 OH involvement Speed ↑ & C 2 H 5 OH not involved Speed ↑ & C 2 H 5 OH involved
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Dept. Computer Science, Korea Univ. Intelligent Information System Lab. 1.5 Bayes’s Theorem Def) Let ■B 1,…,B k : partition of the sample space S ■A : event of S i = 1, 2, …, k Bayes’ thm ■Probability of a particular B i, given that an event A has occured 7
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Dept. Computer Science, Korea Univ. Intelligent Information System Lab. 1.5 Bayes’s Theorem ■e.g. (p.35 ex. 1. 5. 2) A spring in selected at random, probability that it is defective If the selected spring is found to be defective, Probability that it was produced by m/c Ⅲ 8 m/c Ⅰ m/c Ⅱ m/c Ⅲ Defective rate2%1%3% Production portion35%25%40%
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Dept. Computer Science, Korea Univ. Intelligent Information System Lab. 1.5 Bayes’s Theorem ■e.g. pap smear : used to detect cervical cancer ■Cervical cancer : 8/100,000 9
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Dept. Computer Science, Korea Univ. Intelligent Information System Lab. 1.5 Bayes’s Theorem Bayes thm ■P(patient : cancer | test result = +) ■i.e. for ∀ 10 6 positive pap smears, only 354 represents true cases of cervical cancer 10
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Dept. Computer Science, Korea Univ. Intelligent Information System Lab. Homework HW ■[1.1] 4, 6, 10 ■[1.2] 10 ■[1.3] 4, 10, 12 ■[1.4] 2, 6, 8, 10, 12 ■[1.5] 2, 6, 8 11
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