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A problem set from the electrical and computer engineering (ece) 413 course at the university of illinois, spring 2005. It includes five problems covering topics such as tennis game probabilities, senate voting, maximum-likelihood decision rules, and bayesian decision making. Students are required to read specific chapters from ross and use the class webpage notes for decision-making. The problems involve calculating probabilities, finding maximum-likelihood and maximum a posteriori decision rules, and understanding bayes decision making.
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University of Illinois Spring 2005
Due: Wednesday March 9 at the beginning of class. Reading: Ross, Chapters 3, 4, 5, and the notes on decision-making on the class web page
This Problem Set contains five problems
(a) What are the probabilities that the scores reach these 6 possible terminal values? (Hint for those whose drug of choice is MTV and not ESPN: the player who wins the last point in a game also wins the game. Thus, the probability of A winning 4-2 is not
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p^4 q^2 .) (b) What is the probability that A wins the game? Denote this result as f (p). (c) A little thought will show, I hope!, that B wins the game with probability f (1−p). Explain from first principles why f (p) should have the following properties and determine if your answer to part (b) satisfies these properties: f (0) = 0, f (0.5) = 0. 5 , f (1) = 1. Does this mean that f (p) is a linear function of p? (d) Find the first two terms of the Taylor series for f (p) in the neighborhood of p = 0. 5 and determine the effect on the probability of A winning the game if p = 0.5 + where is a small number.
(a) Let A, B, C, and D respectively denote the events that the four groups vote to eliminate all income taxes on capital gains. Suppose that the probabilities of these independent events are P (A) = 0. 9 , P (B) = 0. 6 , P (C) = 0.5 and P (D) = 0.2. What is the probability that the bill passes? (b) The President vetoes the bill as a budget-breaker. Let E, F, G, and H respectively denote the independent events that the four groups support the motion to override the veto. If these events have probabilities P (E) = 0. 99 , P (F ) = 0. 4 , P (G) = 0.6, and P (H) = 0.1, what is the probability that the motion to override the veto passes? Political innocents are reminded that a simple majority (51 or more votes) is required to pass a bill, and a two-thirds majority (67 or more votes) to override a veto.
(a) Having observed Y, what is the receiver’s maximum-likelihood decision rule as to which signal was transmitted? (b) The receiver knows the pmf of X. What is the receiver’s maximum a posteriori probability (MAP) decision rule?
(a) What is his maximum-likelihood decision rule as to whether the pitch was a fast ball, curve ball or slider? (b) Now suppose that after cheering the hit, the fan returns to his seat and finds P (H) = 0.25 listed in the program guide. Having lasted in ECE 413 through Problem Set 6, he can compute P (F ), P (C) and P (S). But, since he dropped the course immediately after Hour Exam I, please help him compute his maximum a posteriori probability decision rule as to what kind of pitch it was.
(a) What is the professor’s maximum-likelihood decision rule? (b) What is the probability that an excellent student is mistakenly labeled as good? What is the probability that an excellent student is mistakenly labeled as average? What is th probability that an average student is classified either as good or as excellent? (c) If P (H 0 ) = 0. 2 , P (H 1 ) = 0.55, and P (H 2 ) = 0.25, what is the probability that the maximum-likelihood decision rule mis-classifies students? (d) What is the Bayes decision rule corresponding to these probabilities and what is the probability that the Bayes decision rule mis-classifies students? (e) At the Lake Wobegon campus of the University, 95% of students are excellent and 5% are good (and thus they are all above average!) What is Bayes decision rule in this case? That is, what does the Bayesian professor decide about a student based on the four possible results of the students exam?