SI 534: Asymptotic Statistics

Class Timings: 

• Lectures: Tuesdays and Fridays (2:00 PM - 3:25 PM on both days) at MA 114

• Tutorials: Wednesdays (3:00 PM - 3:55 PM) at MA 114

Grading Policy: Weightages will be as follows

• Midterm Exam: 30% 

• Final Exam: 40%

• Quiz: 30%

Main Reference: 

• A Course in Large Sample Theory written by Thomas S. Ferguson

• Students should be regular in the class and write down the lecture-notes on a regular basis.

Syllabus:

• Review of convergence concepts in probability. 

• Delta-method and variance stabilizing transformations.

• Asymptotic properties of sample moments and quantiles, and related inference procedures. Asymptotic distribution of order statistics and extreme observations. 

• Asymptotic efficiency of estimators. Asymptotic properties of the likelihood-based estimators and related inference procedures. 

• Implementing asymmetric techniques for data analysis (if time permits).

Exercises:

• Problem-solving exercises will be given in the class on a regular basis.

• Quizzes and both exams will have problems similar to the exercises given in the class.

• Students do NOT need to submit the solutions to the exercises given in the class. However, it is strongly recommended to solve them all and write down the solutions for better performance in the quizzes and exams.

Quizzes:

• Quizzes will be given (mostly) in the tutorials. 

• At least 6 quizzes will be given.

• Except the first one, all the quizzes will be announced in the class at least a day in advance. 

• The worst and the second worst quiz scores will be dropped from the grade calculation.

• Both midterm and final exams will have problems similar to the ones given in the quizzes.

Exams:

• Both midterm and final exams will be closed-note exams.

• A significant portion of the exam questions will be similar to the exercises given in the class and the quizzes.