Statistics, Doctoral Minor

Program Overview

The Doctoral Minor in Statistics requires students to complete 12 credits, with a diverse selection of courses from four lists. Students must take at least one course from List 1, which includes introductory statistics and regression analysis. They can take no more than one course from each of Lists 2, 3, and 4, which cover topics such as machine learning, statistical language, and probability theory. This program provides students with a strong foundation in statistics and prepares them for careers in various fields.

Program Outline

Program Outline:

Content and Structure:

• The Doctoral Minor in Statistics requires students to complete a minimum 12 credits, with at least one course from List 1 (see below), and no more than one course from each of Lists 2, 3 & 4 (see below), ensuring a diverse selection of course content.
• Students may take one additional course from the same list, only if an approved substitution has been granted by the Ph.D minor advisor.

Course List:

List 1:

• STAT 349 Introduction to Statistical Methods (3 credits),
• STAT 333 Applied Regression and Analysis (3 credits),
• STAT 451 Machine Learning and Classification (3 credit),
• STAT 453 Introduction to Statistical Language (1 credit),
• STAT 454 Introduction to Deep Neural Network and Generative Models (3 credits),
• STAT461 Financial Statistics (3 credits),
• STAT 471 Introduction to Applied Statistics for the Life Sciences (4 credits)
• STAT 575 Statistical Methods in Spatial Data ( 3 credits )
• STAT 542 Introduction Clinical Trials I ( 3 credits)

List 4: