MATH 464/564 Probability II (Winter 2021)



Instructor: Yevgeniy Kovchegov
e-mail: kovchegy @math. oregonstate.edu
Office Hours: MW 5-6 or by appointment, via Zoom



Meets: live via Zoom MWF 11:00 am - 11:50 am, or prerecorded.

Grading scheme: Homework 60%, Online quizzes 40%

Textbooks:
(1) Charles M. Grinstead and J. Laurie Snell, Introduction to Probability available as a FREE e-book at http://www.dartmouth.edu/~chance/teaching_aids/books_articles/probability_book/book.html
A hard copy of the textbook can be acquired at bookstores such as Amazon.

(2) Mark Huber, Probability: Lectures and Labs available as a FREE e-book at https://www.markhuberdatascience.org/probability-textbook
A hard copy of the textbook can be acquired at bookstores such as Amazon.

Prerequisites: MTH 463/563 and MTH 341. A minimum grade of C- is required in MTH 463/563 and MTH 341.

Syllabus:  PDF file

Homework:   The homework assignments will need to be submitted in PDF format via Canvas and before the respective deadline. Late homework will not be accepted.

Homework #1 (due Monday, January 25):  HW 1 (PDF)

Schedule:
Monday, January 4  Joint probability mass function. Joint probability density function. Independent random variables. Sums of random variables.   Huber: Chapter 13   Lectures 1-6 slides (PDF)
Wednesday, January 6  Sums of random variables. Gamma and beta random variables. Examples.   Grinstead and Snell: Sections 7.1 and 7.2   Huber: Chapter 13   Lectures 1-6 slides (PDF)
Friday, January 8  Gamma and beta random variables. Poisson process.   Grinstead and Snell: Sections 7.1 and 7.2   Huber: Chapters 13 and 21   Lectures 1-6 slides (PDF)
Monday, January 11  Poisson process. Marginal distributions from joint distribution.   Grinstead and Snell: Sections 7.1 and 7.2   Huber: Chapters 13 and 21   Lectures 1-6 slides (PDF)
Wednesday, January 13  Marginal distributions from joint distribution. Expectations of functions of random variables.   Grinstead and Snell: Sections 7.1 and 7.2   Huber: Chapter 13   Lectures 1-6 slides (PDF)
Friday, January 15  Covariance and correlation.   Huber: Chapters 14 and 15   Lectures 1-6 slides (PDF)
Wednesday, January 20  Covariance and correlation. Multivariate normal distribution.   Huber: Chapters 14 and 15   Lectures 7-11 slides (PDF)
Firday, January 22  Covariance and correlation. Multivariate normal distribution.   Huber: Chapters 14 and 15   Lectures 7-11 slides (PDF)