ECE 302: Probabilistic Methods in Electrical and Computer Engineering

Syllabus

• Syllabus

• Overview

Textbook

Our textbook is “Introduction to Probability for Data Science” by Prof. Stanley Chan.

Another great online resource is “Statistical Rethinking: A Bayesian Course with Examples in R and Stan” with freely available notes and homework problems linked here.

Teaching Staff

Instructor: Kent Gauen, gauenk@purdue.edu

Undergraduate TAs (UTA): (Name, Email)

• Omar Elsayed, elsayedo@purdue.edu

• Shounak Mukherjee, mukher53@purdue.edu

Office Hours

Schedule

Grades

The grades will be curved. The breakdown is below:

• Homework: 35%. Lowest score is dropped.

• Midterm Exam 1: 20%

• Midterm Exam 2: 20%

• Final Exam: 25%

Exams

The midterms are scheduled for September 19th and October 31st. Unless the circumstance is exceptional, we do not offer make-up exams.

Midterm 1 will test the topics colored blue. Midterm 2 will test the topics colored green. The Final Exam covers all course content.

Homework

Homework is posted to Gradescope and due Fridays at 11:59pm. Homework solutions are linked on the front page of Brightspace. Homework assignments are graded by randomly selecting a few problems (maybe one or two) and grading for correctness.

DRC

Please submit your requests through the DRC and take your exams through their office.