University of Wisconsin Fall Semester 2006Department of Economics Economics 709Economic Statistics and Econometrics IProfessor Jack PorterSocial Sciences Building #[email protected] Hours: Monday 3:45–5:15 and by app ointmentTA Ping YuSocial Sciences Building #[email protected] Hours: Monday, Wednesday 1:00–2:30Course DescriptionThis course is an introduction to probability theory and statistical inference designed forfirst year economics Ph.D. students.Lectures and SectionsEach week there will be two lectures of 1 1/4 hours. In addition there will be a sectionmeeting once a week in which problems sets and other issues from lecture will be discussed.BooksThe textbook for the course is:Casella, G., and R. L. Berger, (1999), Statistical Inference, 2ndedition, Brooks/ColePress.Other helpful references are:Goldberger, A., A Course in EconometricsHogg, R., and A. Craig, Introduction to Mathematical StatisticsDeGroot, M., Probability and StatisticsMood, A., F. Graybill and D. Boes, Introduction to t he Theory of StatisticsGallant, R., An Introduction to Econometric TheoryProblems Sets and E xamsProblem sets will be assigned approximately weekly and will be discussed in the sectionmeetings. Grades will be based on a midterm exam (30%), a final exam in December (50%),and the problem sets (20%).1Course Outline (Parenthetical chapters/sections refer to Casella and Berger)1. Probability Theory(a) Elementary Probability Theory (1.1–1.2)(b) Conditional Probability, Independence (1.3)(c) Random Variables, Distribution Functions, Functions of Random Variables (1.4–1.6, 2.1)(d) Transformations and Expectations (2.1–2.3)(e) Joint and Conditional Distributions (4.1–4.7)(f) Special Distributions (3)(g) Convergence, Laws of Large Numbers, Central Limit Theorems (5.1–5.2, 5.5)2. Statistical Inference(a) Minimum Variance Unbiased Estimation (7.3)(b) Maximum Likelihood Estimation (7.2.2)(c) Hypothesis Testing (8)(d) Interval Estimation (9)(e) Bayesian Estimation
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