MTH 3410 - Applied Regression Analysis

3 lecture hours 0 lab hours 3 credits

Course Description
This course introduces advanced applied regression analysis topics. The course will emphasize applied statistical modeling for real-world data using statistical software (e.g., R). In particular, this course will cover simple linear regression, multiple linear regression, One-way Analysis of Variance (ANOVA), fixed and random factors, and logistic regression.
Prereq: MTH 2430 or MTH 2450 or MTH 2480 (quarter system prereq: MA 262 or MA 315 or MA 340)
Note: Students may receive credit for only one of MTH 3410 or ACS 3410.
This course meets the following Raider Core CLO Requirement: Think Critically

Course Learning Outcomes
Upon successful completion of this course, the student will be able to:

Perform regression analysis
Apply various model selection procedures for multiple regression
Use the residual analysis to check the assumptions in a regression analysis
Apply ANOVA as special cases of the multiple regression model
Apply logistic regression for binary dependent variable case
Interpret and effectively communicate the results of regression analysis
Use statistical software to perform various regression analyses

Prerequisites by Topic

Basic probability concepts
Inferential statistics

Course Topics

Simple linear regression
Multiple linear regression
Residual analysis
Variable selection
Analysis of Variance (ANOVA)
Logistic regression

Coordinator
Dr. Won Chul Song

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