Statistics (TI1707) Tinbergen Institute 2021-2022 ContentsThe course is intended for students who have a deficiency in probability and statistics. It starts off with the very first principles of probability and quickly passes on to essential statistical techniques. Estimation and testing theory will be reviewed, including maximum likelihood estimators, likelihood ratio test and (least squares) regression. The course is based on John A. Rice, Mathematical Statistics and Data Analysis, Duxbury Press, Belmont, California. From this book we will treat a good deal of the chapters 2-6, 8, 9 and 14. All together the topics will be treated in 7 lectures, of which the first one is a video lecture. Students are required to study the corresponding theory and examples in the book as well as to make accompanying exercises.In the course we treat the following topics. Sample spaces, probability measures, distribution functions, random variables with discrete and continuous distributions, functions of random variables, multivariate distributions, random vectors, independent random variables, conditional distributions, functions of random vectors and their distributions, expectation and variance, covariance and correlation, the law of large numbers, central limit theorem, chi-square and t-distributions, estimation, method of moments, maximum likelihood, large sample theory, confidence intervals, Cramer-Rao bound, hypothesis testing, Neyman-Pearson paradigm, likelihood ratio tests, confidence intervals, linear regression, least squares estimation of regression parameters, testing regression hypotheses. Learning objectivesBy the end of the course students will be able to:- understand the principles of probability, - understand the essential statistical techniques, and - apply fundamental techniques needed for statistical inference. LiteratureJohn A. Rice, Mathematical Statistics and Data Analysis, 2nd Edition, Duxbury Press (1995, ISBN: 053420934-3), or 3rd Edition (2007, ISBN: 0534399428). Both editions can be used for this year's course, the new edition has more examples (also from financial statistics) and exercises. For the third edition there is a list of errata. Second hand copies of the book are sometimes available at Amazon Germany. Browse the web for other offers.Most important are the slides (2020 version) of the first lecture; this lecture will ONLY be presented online. Take notice of these slides before the first lecture on location on September 1, 2021, and preferably also before the first tutorial session.
You may also want to see pdf copies of some slides used in the lectures, or the extra notes complementing some of the material in the book.
PrerequisitesSome knowledge of elementary mathematics. The course Mathematics 1 offers more than enough. Basic knowledge of probability is required up to the level of chapter 1 of Rice. This chapter will NOT be treated in the course and students are supposed to be familiar with its contents. Chapter 2 will not be treated in detail, only highlights. Students should study the many examples of distributions themselves.PeoplePeter Spreij (lecturer), Markus Müller and Richard van Tiggelen (teaching assistants)Locations and ScheduleLectures on location on Wednesdays, 09:30-12:15, starting on 1 September 2021 with Lecture 2. The first lecture will be available online only, to be communicated further. You are supposed to know the contents of the online lecture before the start of the lectures on location. TA sessions on Thursdays, 15:00-17:00, starting on September 2.ExaminationHomework assignments and written exam. Homework has to be handed every week on the due dates determined by the TAs. During the written exam you are allowed to use the book and a pocket calculator. Your final grade F will be a weighted average of your result H of the homework assignments and the result E of the written exam: F=0.85*E+0.15*H. Date and time of the written exam: October 20, 2021? As an example of what could be asked, you could have a look at the collection of exam questions.Interactive websiteYou may be interested in this interactive website where you can experiment yourself with various topics in probability and statistics. The website accompanies the textbook Statistics: The Art and Science of Learning from Data, 4th Edition by Alan Agresti, Christine A. Franklin, Bernhard Klingenberg. (Thanks to Aisha Schmidt, student who took the course in 2019)Programme (at most minor changes expected)
To the Korteweg-de Vries Institute for Mathematics or to the homepage of Peter Spreij. |