Undergraduate 2019-2020

STAT 406 Multiple Linear Regression

Topics in multiple linear regression, estimation of model parameters, inferences, diagnostics, model assumptions, ANOVA formulation.
3

Prerequisites

MATH 350: with minimum grade of D- and STAT 355: with minimum grade of D- and (MATH 131: with minimum grade of D- or STAT 150: with minimum grade of D-)

STAT 409 Sampling Techniques

Introduction to elementary sampling concepts. Includes random sampling, stratified sampling, cluster sampling and systematic sampling. Inferences and assumptions are presented for all sampling methods.
3

Prerequisites

MATH 350: with minimum grade of D- and STAT 355: with minimum grade of D- and (MATH 131: with minimum grade of D- or STAT 150: with minimum grade of D-)

STAT 411 Fundamentals of Data Science

This course is an introduction to the elements of data science. Topics include data visualization, data wrangling, statistical learning and predictive analytics, text mining and spatial data.
3

STAT 422 Directed Studies

Individualized investigation under the direct supervision of a faculty member. (Minimum of 37.5 clock hours required per credit hour.)
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Course Attribute

Variable Title Course

Repeatable Status

Course is repeatable with no limitations