3 classes matched your search criteria.

Spring 2023  |  PA 5044 Section 001: Applied Regression, Accelerated (57579)

Instructor(s)
Class Component:
Lecture
Instructor Consent:
No Special Consent Required
Instruction Mode:
In Person
Enrollment Requirements:
Co-requisite PA 5033 & 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
 
01/17/2023 - 03/13/2023
Mon, Wed 09:45AM - 11:00AM
UMTC, West Bank
Blegen Hall 435
Enrollment Status:
Open (28 of 40 seats filled)
Also Offered:
Course Catalog Description:
Bivariate/multivariate models used in regression analysis, including assumptions behind them/problems that arise when assumptions are not met. Course covers similar topics as PA 5032 but delves deeper into theory/application of methods. prereq: Students who register for PA 5044 must take PA 5044 and PA 5033 in the same semester. The same grade will be issued for PA 5044 and PA 5033 after PA 5033 is completed.
Class Notes:
Register for both PA 5044 and PA 5033 at the same time. http://classinfo.umn.edu/?jannaj+PA5044+Spring2023
Class Description:
Newly revised and updated for Spring 2022!

This course covers the theory and application of basic regression models, and is targeted to students who intend to continue their quantitative training with further coursework and/or who will likely use quantitative methods with regularity in their future career. Through multiple in-class examples and both individual and group projects, students will gain extensive experience with both consuming and producing the results of regression models, with particular emphasis on the challenges that can arise when applying these methods to different contexts. The course covers the same concepts as PA 5032, but with the aim of a deeper understanding of their implementation. The foundation provided in this course will prepare students for more advanced econometrics courses, either offered at the Humphrey school or at other departments in the University.

Section 002 of PA 5044 is the lab section of the course, held on Fridays and taught by the teaching assistant. For more course information, see the main listing for PA 5044 Section 001.
Who Should Take This Class?:
Students who intend to continue their quantitative analysis training with more advanced courses during their graduate studies, and/or those who would like deeper training in basic regression methods. PA 5031/5045 or equivalent is a preferred prerequisite course.
Exam Format:
No exams will be given in this course. Quizzes will be held via Canvas.
Textbooks:
https://bookstores.umn.edu/course-lookup/57579/1233
Past Syllabi:
http://classinfo.umn.edu/syllabi/jannaj_PA5044_Spring2017.pdf (Spring 2017)
http://classinfo.umn.edu/syllabi/jannaj_PA5044_Spring2016.pdf (Spring 2016)
Instructor Supplied Information Last Updated:
5 November 2021

Spring 2023  |  PA 5044 Section 002: Applied Regression, Accelerated (57580)

Instructor(s)
Class Component:
Laboratory
Times and Locations:
First Half of Term
 
01/17/2023 - 03/13/2023
Fri 09:45AM - 11:00AM
UMTC, West Bank
Hubert H Humphrey Center 85
Auto Enrolls With:
Section 001
Enrollment Status:
Open (18 of 20 seats filled)
Course Catalog Description:
Bivariate/multivariate models used in regression analysis, including assumptions behind them/problems that arise when assumptions are not met. Course covers similar topics as PA 5032 but delves deeper into theory/application of methods. prereq: Students who register for PA 5044 must take PA 5044 and PA 5033 in the same semester. The same grade will be issued for PA 5044 and PA 5033 after PA 5033 is completed.
Class Notes:
Register for both PA 5044 and PA 5033 at the same time. http://classinfo.umn.edu/?jannaj+PA5044+Spring2023
Class Description:
Newly revised and updated for Spring 2022!

This course covers the theory and application of basic regression models, and is targeted to students who intend to continue their quantitative training with further coursework and/or who will likely use quantitative methods with regularity in their future career. Through multiple in-class examples and both individual and group projects, students will gain extensive experience with both consuming and producing the results of regression models, with particular emphasis on the challenges that can arise when applying these methods to different contexts. The course covers the same concepts as PA 5032, but with the aim of a deeper understanding of their implementation. The foundation provided in this course will prepare students for more advanced econometrics courses, either offered at the Humphrey school or at other departments in the University.

Section 002 of PA 5044 is the lab section of the course, held on Fridays and taught by the teaching assistant. For more course information, see the main listing for PA 5044 Section 001.
Who Should Take This Class?:
Students who intend to continue their quantitative analysis training with more advanced courses during their graduate studies, and/or those who would like deeper training in basic regression methods. PA 5031/5045 or equivalent is a preferred prerequisite course.
Exam Format:
No exams will be given in this course. Quizzes will be held via Canvas.
Textbooks:
https://bookstores.umn.edu/course-lookup/57580/1233
Past Syllabi:
http://classinfo.umn.edu/syllabi/jannaj_PA5044_Spring2017.pdf (Spring 2017)
http://classinfo.umn.edu/syllabi/jannaj_PA5044_Spring2016.pdf (Spring 2016)
Instructor Supplied Information Last Updated:
5 November 2021

Spring 2023  |  PA 5044 Section 003: Applied Regression, Accelerated (57581)

Instructor(s)
Class Component:
Laboratory
Times and Locations:
First Half of Term
 
01/17/2023 - 03/13/2023
Fri 11:15AM - 12:30PM
UMTC, West Bank
Hubert H Humphrey Center 85
Auto Enrolls With:
Section 001
Enrollment Status:
Open (10 of 20 seats filled)
Course Catalog Description:
Bivariate/multivariate models used in regression analysis, including assumptions behind them/problems that arise when assumptions are not met. Course covers similar topics as PA 5032 but delves deeper into theory/application of methods. prereq: Students who register for PA 5044 must take PA 5044 and PA 5033 in the same semester. The same grade will be issued for PA 5044 and PA 5033 after PA 5033 is completed.
Class Notes:
Register for both PA 5044 and PA 5033 at the same time. http://classinfo.umn.edu/?jannaj+PA5044+Spring2023
Class Description:
Newly revised and updated for Spring 2022!

This course covers the theory and application of basic regression models, and is targeted to students who intend to continue their quantitative training with further coursework and/or who will likely use quantitative methods with regularity in their future career. Through multiple in-class examples and both individual and group projects, students will gain extensive experience with both consuming and producing the results of regression models, with particular emphasis on the challenges that can arise when applying these methods to different contexts. The course covers the same concepts as PA 5032, but with the aim of a deeper understanding of their implementation. The foundation provided in this course will prepare students for more advanced econometrics courses, either offered at the Humphrey school or at other departments in the University.

Section 002 of PA 5044 is the lab section of the course, held on Fridays and taught by the teaching assistant. For more course information, see the main listing for PA 5044 Section 001.
Who Should Take This Class?:
Students who intend to continue their quantitative analysis training with more advanced courses during their graduate studies, and/or those who would like deeper training in basic regression methods. PA 5031/5045 or equivalent is a preferred prerequisite course.
Exam Format:
No exams will be given in this course. Quizzes will be held via Canvas.
Textbooks:
https://bookstores.umn.edu/course-lookup/57581/1233
Past Syllabi:
http://classinfo.umn.edu/syllabi/jannaj_PA5044_Spring2017.pdf (Spring 2017)
http://classinfo.umn.edu/syllabi/jannaj_PA5044_Spring2016.pdf (Spring 2016)
Instructor Supplied Information Last Updated:
5 November 2021

ClassInfo Links - Spring 2023 Public Affairs Classes

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