Statistical Inference – Syllabus


Syllabus

Instructor: Tianyu Zhang

Contact: bidenbaka@gmail.com

Website: tymathdb.com/tutorial/statistical-inference

Level: Senior Undergraduate, Graduate

Time: Spring 2023

Recitation Time: TBD

Prerequisite:

Audience should be comfortable with probability theory, mathematical statistics. It is recommended that the audience is better to be equipped with

knowledge of topology and functional analysis.

Abstract:

Statistical Inference is one of the most important books in the study of statistics, we will talk about statistical concepts and methodologies as well

as some mathematical approaches to them, it is also designed to cover some related research topic in statistics.

Book: Statistical Inference, Casella

Syllabus:

Part I: Basic Concepts

Lecture 1: 5.1 – 5.4

Lecture 2: 5.5, 5.6, 5.8

Lecture 3: 6.1 – 6.2

Lecture 4: 6.3, 6.4, 6.6

Part II: Estimations, Tests, and Evaluations

Lecture 5: 7.1 – 7.2

Lecture 6: 7.3, 7.5

Lecture 7: 8.1 – 8.2

Lecture 8: 8.3, 8.5

Lecture 9: 9.1, 9.2

Lecture 10: 9.3, 9.5

Lecture 11: 10.1 – 10.2

Lecture 12: 10.3, 10.4, 10.6

Part III: Analysis of Variances and Regression Models

Lecture 13: 11.1-11.2

Lecture 14: 11.3, 11.5

Lecture 15: 12.1 – 12.2

Lecture 16: 12.3, 12.4, 12.6

In Recitations we will talk about the exercises in the book, the time is TBD.