In this course, we will equip students with the essential tools and knowledge in statistics that are essential to modern econometric theory. As probability theory lies in the very foundation of statistics, we will build the probability tools we need along the way. In this sense, this course is designed to be self-contained. The students are expected to not only understand the tools but also be able to have a firm understanding of the mathematical mechanisms behind them, in order to prepare for future econometrics training and research.
In the self-paced version, there will be an exam at the end of the course. We will schedule the individual time slots that work well both for the student and the instructor. In addition, you will have access to 5 hours of interaction with the instructor to answer your questions, clarify the material, etc. We can meet using Zoom or you can simply email us your questions and we will provide you with a detailed reply.
There are four modules covering over twenty lectures of approximately two hours each. There is one problem set for each module and one quiz for each lecture. We will ask questions to be answered during the online lectures to measure your attendance. There will be an exam at the end of the course. Assignment of course grades will be based on attendance (10%), quizzes (20%), homeworks (20%) and the exam (50%).
Deadline to enroll is Feb 28, 2023
Instructor: Qinyou Hu, Graduate Student, Economics
Important Course Dates
Stats Camp for Economic PhD Students Self-Paced: May 23, 2022 – April 30, 2023
Any questions? Please e-mail firstname.lastname@example.org