3 classes matched your search criteria.

Spring 2025  |  PA 5032 Section 001: Applied Regression (56886)

Instructor(s)
Class Component:
Lecture
Instructor Consent:
No Special Consent Required
Instruction Mode:
In Person
Enrollment Requirements:
PA: major or minor in Public Policy or Science/Technology/Environmental Policy or PA PhD or Human Rights major or Development Practice major
Times and Locations:
First Half of Term
 
01/21/2025 - 03/17/2025
Mon, Wed 09:45AM - 11:00AM
UMTC, West Bank
Enrollment Status:
Open (0 of 48 seats filled)
Also Offered:
Course Catalog Description:
Bivariate/multivariate models of regression analysis and assumptions behind them. Problems using these models when such assumptions are not met.
Class Notes:
Credit will not be granted if credit has been received for: PA 5046.
Class Description:
Student may contact the instructor or department for information.
Textbooks:
https://bookstores.umn.edu/course-lookup/56886/1253

Spring 2025  |  PA 5032 Section 002: Applied Regression (56897)

Instructor(s)
Class Component:
Laboratory
Times and Locations:
First Half of Term
 
01/21/2025 - 03/17/2025
Fri 09:45AM - 11:00AM
UMTC, West Bank
Hubert H Humphrey Center 85
Auto Enrolls With:
Section 001
Enrollment Status:
Open (0 of 24 seats filled)
Course Catalog Description:
Bivariate/multivariate models of regression analysis and assumptions behind them. Problems using these models when such assumptions are not met.
Class Notes:
Credit will not be granted if credit has been received for: PA 5046.
Class Description:
Student may contact the instructor or department for information.
Textbooks:
https://bookstores.umn.edu/course-lookup/56897/1253

Spring 2025  |  PA 5032 Section 003: Applied Regression (56970)

Instructor(s)
Class Component:
Laboratory
Times and Locations:
First Half of Term
 
01/21/2025 - 03/17/2025
Fri 11:15AM - 12:30PM
UMTC, West Bank
Hubert H Humphrey Center 85
Auto Enrolls With:
Section 001
Enrollment Status:
Open (0 of 24 seats filled)
Course Catalog Description:
Bivariate/multivariate models of regression analysis and assumptions behind them. Problems using these models when such assumptions are not met.
Class Notes:
Credit will not be granted if credit has been received for: PA 5046.
Class Description:
Student may contact the instructor or department for information.
Textbooks:
https://bookstores.umn.edu/course-lookup/56970/1253

ClassInfo Links - Spring 2025 Public Affairs Classes

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