STAT 905 - High-Dimensional Data and Statistical Learning

Credits: 3

Theoretical framework of statistical methods for the analysis of large-scale data with the aim of understanding data mining, supervised and unsupervised statistical learning techniques from a statistical decision theoretic framework. Methods for model selection, dimensionality reduction, multiple testing control, and estimation in high-dimension data. Emphasis on the conceptual underpinning of different tools for analysis of large-scale data and how they relate to each other. Applications in various fields, including the sciences and engineering, using computer software.

Repeat for Credit
N

Requisites:
Prerequisite: (STAT 713 and STAT 771), or (STAT 727 and STAT 760).

Typically Offered
Fall-Even Years

KSIS Course Search

Kansas State University

Course Catalog

STAT 905 - High-Dimensional Data and Statistical Learning