# Mathematical Statistics (Fall 2022)

Welcome to Mathematical Statistics!
Statistics is an exciting field with applications in many disciplines including machine learning and data science, the physical sciences, and the social sciences.
In this class we will cover the fundamentals of statistics from a mathematical perspective.
This means not just learning about statistical tools, but understanding why and how these tools work.
During the course you will develop proficiency in using these tools, as well as communicating about their mathematical foundations and applications.
You are required to have taken MATH-UA 233 Theory of Probability, so the ability to work with basic ideas from probability is expected.

The project description is posted here.

**Instructor**: Tyler Chen

**Email**: tyler.chen@nyu.edu

**Class**: Tu,Th 2-3:15PM; CIWW 109

**Office Hours**: M,Tu 6-7PM, Th 10-11AM; CIWW 905

**Teaching Assistant**: Theodore Plotkin

**Recitation 02**: 3:30-4:45PM; CIWW 201

**Recitation 03**: 11:00-12:15PM; CIWW 201

**Office Hours**: M 2-4PM; zoom: 910 9819 0753

**Syllabus**

**Edstem discussion**

**Gradescope**

**Bagel Institute**

## Schedule

W=Wasserman, CB=Casella & Berger. Numbers are chapter #’s.

**Week**

**Topic**

**Reading**

**Homework/Quiz**

**1.** (8/29)

Probability review

syllabus, W1, W2, W3, CB1, CB2, CB3, CB4

[09/01]
Intro survey (due 09/06)

[link]
**2.** (9/04)

Probability review

**3.** (9/11)

Convergence of RVs, LLN and CLT, Delta method, inverse CDF sampling

**4.** (9/18)

More CLT, Inference

**5.** (9/25)

Inference, Confidence Intervals

**6.** (10/02)

Density estimation

**8.** (10/16)

Method of moments, MLE

**9.** (10/23)

MLE, Review

quiz 4 (10/25)

**10.** (10/30)

Hypothesis testing, p-values

**11.** (11/06)

Baysian Inference

**12.** (11/13)

Baysian Inference, Gaussian process regression

**13.** (11/20)

Linear/Logistic Regression

quiz 6 (11/22)

[pdf], project proposals (due 11/22)

[pdf]
**14.** (11/27)

Classification

**15.** (12/04)

Project work day, Overview of statistics

quiz 7 (12/06)

[pdf]
(note this is before HW7 is due)

**16.** (12/11)

Project presentations

peer project reviews (due 12/14)

[pdf]
**17.** (12/18)

Finals Week (no class)