STAT4052

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STAT 4052 - Statistical Machine Learning II (4 Cr.)

Statistics, School of (10991) TCLA - College of Liberal Arts

Course description

This is the second semester of the core Applied Statistics sequence for majors seeking a BA or BS in statistics. Both Stat 4051 and Stat 4052 are required in the major. The course introduces a wide variety of applied statistical methods, methodology for identifying types of problems and selecting appropriate methods for data analysis, to correctly interpret results, and to provide hands-on experience with real-life data analysis. The course covers basic concepts of classification, both classical methods of linear classification rules as well as modern computer-intensive methods of classification trees, and the estimation of classification errors by splitting data into training and validation data sets; non-linear parametric regression; nonparametric regression including kernel estimates; categorical data analysis; logistic and Poisson regression; and adjustments for missing data. Numerous datasets will be analyzed and interpreted, using the open-source statistical software R and Rstudio.

prerequisites: STAT 4051 and (STAT 4102 or STAT 5102)

Minimum credits

4

Maximum credits

4

Is this course repeatable?

No

Grading basis

A-F - A-F Grade Basis

Discussion

Lecture

Requirements

009341

Fulfills the writing intensive requirement?

No

Typically offered term(s)

Every Fall & Spring