Math 464, Theory of Probability - FALL 2019

Instructor: Vahan Huroyan

Email: vahanhuroyan (at) math (dot) arizona (dot) edu

Section Time: T TH 11:00 - 12:15

Section Room: Communication, Rm 113

Office Hours: Physics-Atmospheric Sciences (PAS) 514: W TH 2:00-3:00; Mathematics 220: T 2:00-3:00

Course Syllabus: [here]

Textbook: Introduction to Probability, by David F. Anderson, Benedek Valkó, Timo Seppäläinen.


Announcements:

  • Lecture 1, Aug. 27: Sample Spaces and Probabilities. (Section 1.1)
  • Lecture 2, Aug. 29: Random Sampling. Infinitely many outcomes. (Sections 1.2 and 1.3)
  • Lecture 3, Sep. 3: Consequences of the Rules of Probability. (Section 1.4)
  • Lecture 4, Sep. 5: Random Variables: a first look. Conditional Probability. (Sections 1.5 and 2.1)
  • Lecture 5, Sep. 10: Bayes' Formula. (Section 2.2)
  • Lecture 6, Sep. 12: Independence. (Section 2.3)
  • Lecture 7, Sep. 17: Independent trials. (Section 2.4)
  • Lecture 8, Sep. 19: Further topics for sampling and independence. (Section 2.5)
  • Lecture 9, Sep. 24: Conditional independence, Probability distributions of random variables. (Sections 2.5, 3.1)
  • Lecture 10, Sep. 26: Probability distributions of random variables. (Section 3.1)
  • Lecture 11, Oct. 1: Cumulative distribution function. (Section 3.2)
  • Lecture 12, Oct. 3: Expectation. (Section 3.3)
  • Lecture 13, Oct. 8: Review
  • Lecture 14, Oct. 10: Midterm 1.
  • Lecture 15, Oct. 15: Expectation. (Section 3.3)
  • Lecture 16, Oct. 17: Variance. (Section 3.4)
  • Lecture 17, Oct. 22: Gaussian distribution. (Section 3.5)
  • Lecture 18, Oct. 24:

  • Homework:

  • HW 1: posted 09/06, due 09/17 ---- 1.2, 1.5, 1.8, 1.13, 1.17, 1.19, 1.33, 1.40.
  • HW 2: posted 09/19, due 10/01 ---- 2.4, 2.7, 2.10, 2.14, 2.18, 2.22, 2.25, 2.31, 2.33, 2.54.
  • HW 3: posted 10/03, due 10/17 ---- 2.24, 2.26, 3.3, 3.4, 3.5, 3.7, 3.8, 3.9, 3.10, 3.12