Course: COMP 639. Probability and Statistics for Data Science (3)

Prerequisites: Completion of MATH 340 or MATH 341 with a grade of “C” or better; COMP 502. Recommended Preparatory: Knowledge of Python programming. A study of fundamental concepts in probability and statistics from a data science perspective. Topics in probability include probability spaces, random variables, multivariate random variables, expectation, convergence of random variables. Topics in statistics include descriptive, frequentist and Bayesian statistics, estimation, hypothesis testing, goodness of fit, analysis of variance, and least squares regression model. Programming will be used to apply the theory to examples and real-world datasets.

Fall-2024 - Schedule of Classes

COMP 639

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