Math 3332: Probability and Inference

General Information

Instructor: Mikhail Lavrov
Location: Mathematics Building 237.
Lecture times: 11:15am-12:05pm on Monday if your last name begins A-L and on Wednesday if your last name begins M-Z.
Textbook: Introduction to Probability, Statistics, and Random Processes by Hossein Pishro-Nik, available online at https://www.probabilitycourse.com/.
Office hours: Wednesday 10am-11am and Friday 11am-12pm, online via Collaborate Ultra.
D2L page: https://kennesaw.view.usg.edu/d2l/home/2199846.

More information is available on D2L, where I will post the syllabus, homework assignments and solutions, exams, and more. This webpage is primarily for posting recorded lectures.

Homework and Exams

There will be eight homework assignments, two midterm exams, and one final exam. The dates are marked below, but you can find and submit the assignments on D2L. No part of your grade will depend on coming to class.

Detailed Schedule

The textbook sections listed below are a good source for what we'll talk about on each day, but we won't always cover everything the textbook covers, or do things in the same order. I am not going to expect you to learn material from the textbook that I don't cover in lectures.

My goal is to have all the recordings for each week posted by the beginning of that week. If you are interested in my slides, you can find them here, but I don't think they are a good replacement for watching the video.

  • Date
    Textbook
    Recordings
    Assignments
  • Mon 1/11
    1.2 Review of Set Theory
     
  • Wed 1/13
    1.3.2 Probability
     
  • Fri 1/15
    1.3.3 Finding Probabilities
     
  • Mon 1/18
    No Class
     
     
  • Wed 1/20
    1.3.4 Discrete Models
     
  • Fri 1/22
    1.3.5 Continuous Models
    HW 1 due
  • Mon 1/25
    1.4 Conditional Probability
     
  • Wed 1/27
    1.4.1 Independence
     
  • Fri 1/29
    1.4.2 Law of Total Probability
     
  • Mon 2/1
    1.4.3 Bayes' Rule
     
     
  • Wed 2/3
    11.2 Discrete-Time Markov Chains
     
     
  • Fri 2/5
    1.4 Conditional Probability
     
    HW 2 due
  • Mon 2/8
    2.1 Combinatorics
     
     
  • Wed 2/10
    2.1.1-2 Ordered Sampling
     
     
  • Fri 2/12
    2.1.3 Unordered without Replacement
     
    HW 3 due
  • Mon 2/15
    2.1.4 Unordered with Replacement
     
     
  • Wed 2/17
    Counting review
     
     
  • Fri 2/19
    Exam 1 (due at 11:59pm)
     
     
  • Mon 2/22
    3.1 Random Variables
     
     
  • Wed 2/24
    3.1.5 Special Distributions
     
     
  • Fri 2/26
    3.2.2 Expectation
     
    HW 4 due
  • Mon 3/1
    3.1.5 Special Distributions
     
     
  • Wed 3/3
    3.2.3 Functions of Random Variables
     
     
  • Fri 3/5
    3.2.4 Variance
     
     
  • 3/8-3/14
    Spring Break: No Class
     
     
  • Mon 3/15
    3.1.4 Independent Random Variables
     
     
  • Wed 3/17
    More Variance Calculations
     
     
  • Fri 3/19
    6.1.3 Moment Generating Functions
     
    HW 5 due
  • Mon 3/22
    6.2 Probability Bounds
     
     
  • Wed 3/24
    5.1 Two Discrete Random Variables
     
     
  • Fri 3/26
    Conditioned Random Variables
     
     
  • Mon 3/29
    5.1.3 Conditioning and Independence
     
     
  • Wed 3/31
    9.1.1 Prior and Posterior
     
     
  • Fri 4/2
    4.1 Continuous Random Variables
     
    HW 6 due
  • Mon 4/5
    4.1.1 Probability Density Function
     
     
  • Wed 4/7
    4.2.2 Exponential Distribution
     
     
  • Fri 4/9
    Exam 2 (due at 11:59pm)
     
     
  • Mon 4/12
    4.1.2 Expected Value and Variance
     
     
  • Wed 4/14
    4.1.3 Functions of Random Variables
     
     
  • Fri 4/16
    4.2.3 Normal Distribution
     
    HW 7 due
  • Mon 4/19
    11.1 Poisson processes
     
     
  • Wed 4/21
    5.2 Two Continuous Random Variables
     
     
  • Fri 4/23
    5.2.3 Conditioning and Independence
     
     
  • Mon 4/26
    Mixture Distributions
     
     
  • Wed 4/28
    4.3 Mixed Random Variables
     
     
  • Fri 4/30
    8.4 Hypothesis Testing
     
    HW 8 due
  • Mon 5/3
    9.1 Bayesian Inference
     
     
  • Wed 5/5
    Final Exam (due 5/6 at 11:59pm)
     
     
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