SI 424: Statistical Inference 1
Taught at IIT Bombay
Teacher: Parthanil Roy
Lectures: Mondays and Thursdays (2:00 PM - 3:25 PM on both days) at MA 114
Tutorials: Wednesdays (2:00 PM - 3:00 PM) at MA 114
Grading Policy: Weightages will be as follows
Midterm Exam: 30%
Final Exam: 40%
Quiz: 30%
Main Reference:
Statistical Inference (Second Edition) by G. Casella and R. Berger
Students should be regular in the class and write down the lecture-notes on a regular basis.
Syllabus:
Distributions of functions of random variables, Sampling distributions, Order statistics, Sufficiency and completeness, Exponential family of distributions, Methods of estimation (Method of Moments, MLE and Bayesian), Unbiased estimators, Evaluating estimators, UMVUEs, Testing, Likelihood Ratio tests, UMP tests, Unbiased tests, Interval estimation, Consistent and efficient estimators.
Exercises:
Problem-solving exercises will be given in the class on a regular basis.
Both midterm and final 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 exams.
Quizzes will be given (mostly) in the tutorials.
At least 8 quizzes will be given.
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 a closed-note exams.
A significant portion of the exam questions will be similar to the exercises given in the class and the quizzes.