APMA 3100
Probability
Course Description
A calculus-based introduction to probability theory and its applications in engineering and applied science. Includes counting techniques, conditional probability, independence, discrete and continuous random variables, probability distribution functions, expected value and variance, joint distributions, covariance, correlation, the Central Limit theorem, the Poisson process, an introduction to statistical inference. Students must have completed (APMA 2120 or MATH 2310 or MATH 2315) AND (CS 1110 or CS 1111 or CS 1112 or CS 1113 or successfully completed the CS 1110 place out test).
Instructors
Christian Hellings
Fall 2026
Hui Ma
Fall 2026
Matthew McMillan
Fall 2026
Megan Ryals
Fall 2026
James Lark
Summer 2026
Jing Yang
Spring 2026
Farzad Dizaji
Spring 2025
Farzad Shafiei Dizaji
Spring 2025
Deepyaman Maiti
Spring 2025
To Announced
Fall 2024
Jennifer Marley
Spring 2024
Joshua Choi
Spring 2023
Roman Krzysztofowicz
Spring 2023
Jundong Li
Spring 2023
Cong Shen
Fall 2022
Faculty Staff
Spring 2022
Bernard Fulgham
Fall 2021
Nikolaos Sidiropoulos
Fall 2020
Meiqin Li
Spring 2020
Jie Lian
Spring 2019
Elsa Harris
Spring 2017
Daria Snider
Spring 2017
Julia Spencer
Summer 2016
Thomas Baber
Summer 2015
Rajinder Mavi
Spring 2014
Todd Delong
Fall 2012
Gianluca Guadagni
Fall 2011
Radu Dascaliuc
Fall 2009