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STATISTICAL LEARNING

STAT 615
Course Description

The development of a variety of mathematical theories and statistical concepts (1) to understand the properties of those models and methods used for the purpose of prediction from data or decision making from data, and (2) to criticize such models, methods and their consequences. Specifically, the theories and tools that will be developed will include complexity theory, Hilbert spaces, Gaussian processes, Variational Analysis, and concentration inequalities.

Prerequisites

Declared in Statistics: Statistics and Data Science MS, Data Science MS, Data Engineering MS, or Statistics VISP

Satisfies

This course does not satisfy any prerequisites.

Credits

Not Reported

Offered

Not Reported

Grade Point Average
3.43

-3.41% from Historical

Completion Rate
100%

0.64% from Historical

A Rate
21.74%

-62.2% from Historical

Class Size
23

-55.91% from Historical

Cumulative Grade Distribution

Instructors (2026 Summr)

Sorted by ratings from Rate My Professors

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