UW-Madison ECON 709 - ECON 709 Syllabus (2 pages)

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ECON 709 Syllabus



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ECON 709 Syllabus

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Pages:
2
School:
University of Wisconsin, Madison
Course:
Econ 709 - Economic Statistics and Econometrics I
Economic Statistics and Econometrics I Documents
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University of Wisconsin Department of Economics Fall Semester 2011 Economics 709 Economic Statistics and Econometrics I Professor Xiaoxia Shi Social Sciences Building 6428 xshi ssc wisc edu Office Hours Monday 1 30 2 30pm and by appointment TA SeoJeong Jay Lee Social Sciences Building 7308 slee279 wisc edu Office Hours 11am 12pm Friday Course Description and Prerequisite This 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 Organizations Each week there will be two lectures of 1 1 4 hours M W 11 00am 12 15pm at PSYCHOLOGY 121 In 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 Theory 1 Elementary Probability Theory 2 Conditional Probability Independence 3 Random Variables Distribution Functions Functions of Random Variables 4 Transformations and Expectations 5 Joint and Conditional Distributions 6 Special Distributions 7 Convergence Laws of Large Numbers Central Limit Theorems 2 Statistical Inference 1 Maximum Likelihood Estimation and Simple Linear Models 2 Point Estimation 3 Interval Estimation 4 Bayesian Estimation 5 Hypothesis Testing Recording of the class is prohibited Students with disabilities please see me as soon as possible if you will need accomodation


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