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ENEE324: Engineering Probability – Course Syllabus Fall 2013 Instructor: Joseph JaJa Course Objectives: Axioms of probability; conditional probability and Bayes' rule; random variables, probability distribution and densities: functions of random variables: weak law of large numbers and central limit theorem. Introduction to statistical inference and the Bernoulli and Poisson processes. Prerequisite: ENEE 322 and completion of all lower-division technical courses in the ECE curriculum Textbook (required): Bertsekas and Tsitsiklis, Introduction to Probability, Second Edition, Athena Scientific 2008. Core Topics: 1. Introduction to Probability (Chapter 1) Sample Space and Events Axioms of Probability Computing Probabilities Conditional Probability and Independence Independence Counting 2. Discrete Random Variables (Chapter 2) Discrete Random Variables and Probability Mass Function Functions of a Random Variable Expected Value, Variance and Standard Deviation Joint Probability Functions Conditional Distributions and Conditional Expectations Independent Random Variables 3. General Random Variables (Chapter 3) Continuous Random Variables and Probability Density Functions Cumulative Distribution Functions Normal Random Variables Multiple Random Variables Conditional Distributions and Conditional Expectations 4. Functions of Random Variables (Chapter 4) Derived Distributions Covariance and Correlation Transforms Sum of a Random Number of Independent Random Variables 5. Limit Theorems (Chapter 5) Markov and Chebyshev Inequalities The Weak Law of Large Numbers Convergence in Probability The Central Limit Theorem 6. Statistical Inference (Chapter 9) Parameter Estimation Confidence Intervals Binary Hypothesis Testing 7. Stochastic Processes (Chapter 6) The Bernoulli Process The Poisson Process Grading Policy: Midterm Exams: 25% (Midterm I, October 9). 30% (Midterm II. November 13). Homework and Quizzes: 10% (assigned after each lecture, collected by the end of the next lecture, returned in recitations) Final Exam: 35% (Comprehensive) Late Assignments: No late assignments will be accepted but the assignment with the lowest score will not be counted. Office Hours by Instructor (3433 A.V. Williams Bldg): M, W 4-5:30, and by email appointment. Additional office hours will be offered by the TAs. Contact Information: [email protected]; 301-405-1925. The University of Maryland, College Park has a nationally recognized Code of Academic Integrity, administered by the Student Honor Council. This Code sets standards for academic integrity at Maryland for all undergraduate and graduate students. As a student you are responsible for upholding these standards for this course. It is very important for you to be aware of the consequences of cheating, fabrication, facilitation, and plagiarism. For more information on the Code of Academic Integrity or the Student Honor Council, please visit http://www.studenthonorcouncil.umd.edu/whatis.html .