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Semester | fall semester 2022 |
Course frequency | Every fall sem. |
Lecturers | Christian Kleiber (christian.kleiber@unibas.ch, Assessor) |
Content | The course intends to provide an overview of useful (and often cheap!) results in probability, results that are beyond the usual undergraduate "(Probability and) Statistics for Business and Economics" course but still far away from industry-strength probability. In economics departments, probability is often narrowly seen as an input for econometrics, or empirical fields more broadly. The present course will attempt to provide a broader view: applied probability not only as a basis for econometrics and statistics, but also for a better understanding of stochastic models in economics, finance and management science. Measure theory will not be developed, but it will be explained why this more abstract version exists and what it looks like. As always, the limiting factor is mathematics. We aim at an intermediate level emphasizing practically useful results and computation, deeper results will only be sketched or quoted. The course will be an eclectic mix of loosely related topics. It will not follow a textbook; it should be possible to just sample parts. Topics will include computations of expectations and variances, an overview of useful distributions and methods for constructing new ones, methods for bounding probabilities and expectations (possibly including uses in machine learning), order statistics and their applications, possibly the Poisson process. In addition to the topics from previous years I will try to include something on stochastic orders and/or dependence concepts, possibly an overview of limit theorems. There will be no data analysis (obviously), but software for simulations or plotting (!), such as R or Matlab, can be helpful. |
Learning objectives | Overview of probabilistic tools beyond the undergraduate level. |
Bibliography | The course will not follow a specific textbook. General references include Gupta AK, Zeng WB, Wu Y (2010). Probability and Statistical Models (Foundations for Problems in Reliability and Financial Mathematics), Springer. [available as eBook] Gut A (2009). An Intermediate Course in Probability, 2nd ed. Springer. [available as eBook] Hong Y (2018). Probability and Statistics for Economists, World Scientific. Linton O (2017). Probability, Statistics and Econometrics, Academic Press. Monfort A (1996). Cours de probabilit'es, 3rd ed, Economica. Ross S (2019). A First Course in Probability, 10 ed, Pearson. Wasserman L (2005). All of Statistics, Springer. |
Comments | This is a course simultaneously addressing beginning PhD students and MSc students with sufficient preparation. It will proceed more quickly than typical MSc level courses. |
Weblink | Weblink |
Admission requirements | Students majoring in business and economics: BA completed. In addition, successful completion of Econometrics (MSc) is strongly recommended. Other participants: Some background in statistics and mathematics, roughly 'engineering level'. |
Course application | Registration: Please register for the course and the subsequent exam by writing an Email to christian.kleiber@unibas.ch until August 26, 2022 at the latest. Please make sure that you have registered for the fall semester and paid the semester fees before you register for this course. In case of non-participation after registration it will be noted as "nicht erschienen" in the transcript. |
Language of instruction | English |
Use of digital media | No specific media used |
Course auditors welcome |
Interval | Weekday | Time | Room |
---|---|---|---|
Block | See individual dates |
Modules |
Modul: Fachlich-methodische Weiterbildung (Doctoral Studies - Faculty of Business and Economics) Modul: Specific Electives in Economics (Master's Studies: Business and Economics) Module: Core Courses in Data Science and Computational Economics (Master's Studies: Business and Economics) Module: Electives (Master's Studies: Business and Economics (Start of studies before 01.08.2021)) Module: Field Electives in Economics and Public Policy (Master's Studies: Economics and Public Policy) Module: Specific Electives in Business and Economics (Master's Studies: Business and Economics) Module: Specific Electives in Data Science and Computational Economics (Master's Studies: Business and Economics) |
Assessment format | record of achievement |
Assessment details | For PhD students, there will be an oral exam. For MSc students, depending on the number of participants (up to 15 or more), there will be an oral or a written exam. In addition, there will be (at least) one assignment, accounting for 30% of the overall grade. |
Assessment registration/deregistration | Registration/deregistration: teaching staff |
Repeat examination | no repeat examination |
Scale | 1-6 0,1 |
Repeated registration | as often as necessary |
Responsible faculty | Faculty of Business and Economics , studiendekanat-wwz@unibas.ch |
Offered by | Faculty of Business and Economics |