STAT711 | Statistical Theory 1

Here's grading for the first half of the course:

For the first half the course, we will closely follow this Lecture Notes. Here are other resources that might be useful:

Textbook for Data 140: Probability for Data Science by Ani Adhikari and Jim Pitman.
Statistical Inference by Roger L. Casella, George Berger. Duxbury Press.
Theoretical Statistics - Topics for a Core Course by Robert W. Keener. Springer.
Robert Nowak’s lecture notes on Statistical Signal Processing and Learning Theory.

No.	Topic	Notes	Homework
1	Basic set theory and probability
2	Counting
3	Conditional probability
4	Independence and random variables
5	Multiple random variables
6	Variance and Standard Deviation		Homework 1
7	Probability distributions
8	Probability density functions
9	Examples of probability distributions
10	Poisson and Normal distributions
11	Cumulative distribution functions
12	Marginal and conditional distributions, Independence		Homework 2
13	Transformation of random variables
14	Moments and MGF
15	Random samples	Lecture 15
16	Sample mean and sample variance	Lecture 16
17	Sufficient statistics	Lecture 17
18	Minimal sufficient statistics	Lecture 18	Homework 3
19	Complete statistics, Basu's theorem	Lecture 19
20	Rao-Blackwell theorem, UMVU	Lecture 20
21	Maximum Likelihood estimators	Lecture 21
22	Cramér-Rao inequality	Lecture 22
23	Bayesian inference	Lecture 23	Homework 4
24	Minimax estimators	Lecture 24
25	Neyman-Pearson lemma	Lecture 25
26	Monotone likelihood ratio tests	Lecture 26
27	Likelihood ratio tests	Lecture 27
28	Confidence intervals	Lecture 28	Homework 5