Bayesian Econometrics was cancelled last year because of low enrollment. Now we are offering it again this term Those who go through this course will acquire world class skills in Bayesian econometrics, which are very useful in doing data analysis for research related to M Phil and Masters theses. These methods allow new ways to analyze and interpret data which are not available with standard econometric techniques.
The course will focus on interpretation and implementation, and not proofs and mathematics. It is designed to be user friendly, and teach student how to DO Bayesian econometrics on real world data sets in context of applications. In comparison with current available textbooks, this approach is very light on mathematics. Nonetheless, some mathematical work is required. We have been very careful to select only the minimum essentials required, and also ensured that the material can be grasped by students with average background available here. IN RETURN, we ask the student to make the efforts necessary to understand the course.
The course materials will be available on following website:
Bayesian Econometrics
Before starting the course, some preliminary basic materials must be mastered. These are covered in lectures which are described here.
The course will focus on interpretation and implementation, and not proofs and mathematics. It is designed to be user friendly, and teach student how to DO Bayesian econometrics on real world data sets in context of applications. In comparison with current available textbooks, this approach is very light on mathematics. Nonetheless, some mathematical work is required. We have been very careful to select only the minimum essentials required, and also ensured that the material can be grasped by students with average background available here. IN RETURN, we ask the student to make the efforts necessary to understand the course.
The course materials will be available on following website:
Bayesian Econometrics
Before starting the course, some preliminary basic materials must be mastered. These are covered in lectures which are described here.
PRELIMINARIES: This material should be studied and mastered BEFORE starting the course
Preliminary Introductory Lecture 0: Islamic Approaches to Knowledge:
Lect 1: is about drawing histograms for data == Lec 7 of Introduction to Statistics == Lec 2 of Applied Econometrics
Lec 2: Making Kernel Density representation of data -- an improvement over histograms == Lec 8 of Intro Stats
Lec 3: Basic Theory of Binomial Random Variables - De Moivre's Theorem == Builds upon Lec 13 of Intro Stats, and parts of Lec 08 Intro to App Econometrics
Please study this material before the start of the course.
Asad Zaman
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