IE 2117 - FOUNDATIONS OF STATISTICS
Minimum Credits: 3
Maximum Credits: 3
This course equips first year PhD students with essential tools for statistical modeling and analysis. The main focus of this course is on mathematical statistics and bringing out different features of Frequentist, Fisherian and Bayesian approaches to statistical inference, as well as foundations of modern statistics as it interfaces with machine learning and other data-driven paradigms. Students will also get exposure to decision theory and related paradigms for evaluating statistical procedures. Strong background in probability theory and undergraduate statistics is assumed.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad Letter Grade
Click here for class schedule information.
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