hydai99 / data-science-5620-fall-2021

Course website for the Fall 2021 semester of Data Science 5620 at Vanderbilt University.

<script src="https://kit.fontawesome.com/889acaf6e2.js"></script>

Probability & Inference

Overview

This course covers the fundamentals of probability theory and statistical inference. Topics in probability include random variables, distributions, expectations, moments, Jensen’s inequality, law of large numbers, central limit theorem. Topics in inference include maximum likelihood, point estimation (Bayesian, frequentist, and likelihood versions); hypothesis and significance testing; re-sampling techniques. Complex mathematical proofs will be illustrated with computational solutions.

Instructor

Thomas G. Stewart, PhD
Assistant Professor
2525 West End Ave, Suite 1100, Room 11128A
[email protected]
thomasgstewart

Teaching assistants

Lead: Megan Hollister
PhD Biostatistics Candidate
[email protected]
murraymegan

Soyeon Park
MS Data Science Candidate
[email protected]
soyeon-park1121

Yan Yan
PhD Biostatistics Candidate
[email protected]
sallymeeyan

Instruction & Office hours

Format of the class: Face-to-Face lectures will be held in the Sony Building room 2001A. Office hours will be held 4 times each week, one of which will be virtual. Please note: Circumstances may require the face-to-face portion of the class to be online.

Lectures: Sony 2001A (Face-to-Face) Monday and Wednesday @ 9am GMT-5

Office Hours:

1. Monday @ 10:15am GMT-5 - Sony 2071
2. Tuesday @ 9:30am GMT-5 - Sony 2020
3. Wednesday @ 3pm GMT-5 - Online, link posted in Slack
4. Friday @ 1pm GMT-5 - Sony 2020

Textbooks

Probability and Statistics for Data Science
by Norman Matloff
ISBN-10: 1138393290
ISBN-13: 978-1138393295

Introductory Statistics with Randomization and Simulation
by David M Diez, Christopher D Barr, Mine Çetinkaya-Rundel
ISBN-10: 1500576697
ISBN-13: 978-1500576691
Available as a free PDF download (link)

Optional reference texts available in the DSI Library

Statistics
by David Freedman, Robert Pisani, Roger Purves
ISBN-10: 0393929728
ISBN-13: 978-0393929720
Level: Geared toward an undergraduate, freshman course

Statistical Inference
by George Casella, Roger L. Berger
ISBN-10: 0534243126
ISBN-13: 978-0534243128
Level: Introductory mathematical statistics text for graduate level course.

Computing

The course will be taught using R (link).

Communication

Students will be invited to a course slack channel. Questions related to course logistics, content, homework, quizzes, or the final project should be posted in the slack channel. Individual questions should be sent to the instructor and/or TA by direct slack message.