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Regression Methods

Instructor:
Solomon W. Harrar
648
Credits:
4.0
201
Building:
TBD
Room:
TBD
Semester:
Spring 2025
Start Date:
End Date:
Name:
Regression Methods
Requisites:

Prereq: STA 645 and admission to the Master of Applied Statistics program or permission of the instructor.

Class Type:
LEC
TBD
TBD
Days:
TBD
Note:
Enrollment is limited to students enrolled in the Master of Applied Statistics (Online) Program. Please contact stat-dgs@uky.edu for registration information.

Statistics (STA) 648 is an applied regression course that emphasizes data analysis and interpretation. Generally, regression is a collection of methods for determining and using models that explain how a response variable (dependent variable) relates to one or more explanatory variables (predictor variables). This course aims to teach students about different regression models, their corresponding assumptions, and how to interpret the estimated models. Statistical computing will be central to understanding material in this course as the student will be required to perform analyses on real datasets using the learned methods.

Statistics (STA) 648 is an applied regression course that emphasizes data analysis and interpretation. Generally, regression is a collection of methods for determining and using models that explain how a response variable (dependent variable) relates to one or more explanatory variables (predictor variables). This course aims to teach students about different regression models, their corresponding assumptions, and how to interpret the estimated models. Statistical computing will be central to understanding material in this course as the student will be required to perform analyses on real datasets using the learned methods.

STA