University of Wisconsin Fall Semester 2011Department of Economics Economics 709Economic Statistics and Econometrics IProfessor Xiaoxia ShiSocial Sciences Building #[email protected] Hours: Monday 1:30-2:30pm and by appointmentTA SeoJeong (Jay) LeeSocial Sciences Building #[email protected] Hours: 11am - 12pm Friday Course Description and PrerequisiteThis course is an introduction to probability theory and statistical inference designed for first year economics Ph.D. Students.Students will be expected to have taken calculus, linear algebra and some introductory probability and statistics.OrganizationsEach week there will be two lectures of 1 1/4 hours. M/W 11:00am – 12:15pm at PSYCHOLOGY 121In addition there will be 3 identical TA sessions each Friday in which problems sets and other issues from lecture will be discussed.TA session time:9:55am - 10:45am (Ingraham 115)3:30pm - 4:20pm (Soc Sci 5322)4:35pm - 5:25pm (Soc Sci 5322)Grading:Problem sets will be assigned approximately weekly and will be discussed in the TA sessions. Grades will be based on a midterm exam (30%), a final exam in December (50%) and the problem sets (20%).Books:The textbook for the course is:Hogg, Craig and McKean, 2004, "Introduction to Mathematical Statistics," 6th edition, Prentice Hall. (HCM)Problem set questions will primarily be from this book.References:Billingsley, 1979, "Probability and Measure," New York: Wiley (A good book for an introduction to measure theoretic probability theory)Casella and Berger, 2002, "Statistical Inference," 2nd edition, Pacific Grove, CA: Duxbury. (A book at a somewhat higher level than that of HCM)Course Outline (Tentative)1. Probability Theory1. Elementary Probability Theory2. Conditional Probability, Independence3. Random Variables, Distribution Functions, Functions of Random Variables4. Transformations and Expectations5. Joint and Conditional Distributions6. Special Distributions7. Convergence, Laws of Large Numbers, Central Limit Theorems2. Statistical Inference1. Maximum Likelihood Estimation and Simple Linear Models2. Point Estimation3. Interval Estimation4. Bayesian Estimation5. Hypothesis Testing**Recording of the class is prohibited.**Students with disabilities: please see me as soon as possible if you will need