23 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

Spring 2022  |  PA 5044 Section 001: Applied Regression, Accelerated (58948)

Instructor(s)
Class Component:
Lecture
Instructor Consent:
No Special Consent Required
Instruction Mode:
In Person Term Based
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
 
01/18/2022 - 03/14/2022
Mon, Wed 09:45AM - 11:00AM
UMTC, West Bank
Blegen Hall 135
Enrollment Status:
Open (34 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: 5031 or equiv, or instr consent
Class Notes:
http://classinfo.umn.edu/?jannaj+PA5044+Spring2022
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/58948/1223
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 2022  |  PA 5044 Section 002: Applied Regression, Accelerated (58949)

Instructor(s)
Class Component:
Laboratory
Times and Locations:
First Half of Term
 
01/18/2022 - 03/14/2022
Fri 09:45AM - 11:00AM
UMTC, West Bank
Hubert H Humphrey Center 85
Auto Enrolls With:
Section 001
Enrollment Status:
Open (20 of 21 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: 5031 or equiv, or instr consent
Class Notes:
http://classinfo.umn.edu/?jannaj+PA5044+Spring2022
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/58949/1223
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 2022  |  PA 5044 Section 003: Applied Regression, Accelerated (58950)

Instructor(s)
Class Component:
Laboratory
Times and Locations:
First Half of Term
 
01/18/2022 - 03/14/2022
Fri 11:15AM - 12:30PM
UMTC, West Bank
Hubert H Humphrey Center 85
Auto Enrolls With:
Section 001
Enrollment Status:
Open (14 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: 5031 or equiv, or instr consent
Class Notes:
http://classinfo.umn.edu/?jannaj+PA5044+Spring2022
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/58950/1223
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 2020  |  PA 5044 Section 001: Applied Regression, Accelerated (57556)

Instructor(s)
Class Component:
Lecture
Instructor Consent:
No Special Consent Required
Instruction Mode:
In Person Term Based
Times and Locations:
First Half of Term
 
01/21/2020 - 03/16/2020
Mon, Wed 09:45AM - 11:00AM
UMTC, West Bank
Hubert H Humphrey Center 25
Enrollment Status:
Open (25 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 uses more mathematical notation/delves deeper into theory/application of methods. prereq: [5031 or equiv} or instr consent
Class Notes:
http://classinfo.umn.edu/?hicks208+PA5044+Spring2020
Class Description:
Student may contact the instructor or department for information.
Textbooks:
https://bookstores.umn.edu/course-lookup/57556/1203

Spring 2020  |  PA 5044 Section 002: Applied Regression, Accelerated (57557)

Instructor(s)
Class Component:
Laboratory
Times and Locations:
First Half of Term
 
01/21/2020 - 03/16/2020
Fri 09:45AM - 11:00AM
UMTC, West Bank
Hubert H Humphrey Center 85
Auto Enrolls With:
Section 001
Enrollment Status:
Open (17 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 uses more mathematical notation/delves deeper into theory/application of methods. prereq: [5031 or equiv} or instr consent
Class Notes:
http://classinfo.umn.edu/?hicks208+PA5044+Spring2020
Class Description:
Student may contact the instructor or department for information.
Textbooks:
https://bookstores.umn.edu/course-lookup/57557/1203

Spring 2020  |  PA 5044 Section 003: Applied Regression, Accelerated (57558)

Instructor(s)
Class Component:
Laboratory
Times and Locations:
First Half of Term
 
01/21/2020 - 03/16/2020
Fri 11:15AM - 12:30PM
UMTC, West Bank
Hubert H Humphrey Center 85
Auto Enrolls With:
Section 001
Enrollment Status:
Open (8 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 uses more mathematical notation/delves deeper into theory/application of methods. prereq: [5031 or equiv} or instr consent
Class Notes:
http://classinfo.umn.edu/?hicks208+PA5044+Spring2020
Class Description:
Student may contact the instructor or department for information.
Textbooks:
https://bookstores.umn.edu/course-lookup/57558/1203

Spring 2019  |  PA 5044 Section 001: Applied Regression, Accelerated (58222)

Instructor(s)
Class Component:
Lecture
Instructor Consent:
No Special Consent Required
Instruction Mode:
In Person Term Based
Times and Locations:
First Half of Term
 
01/22/2019 - 03/11/2019
Mon, Wed 09:45AM - 11:00AM
UMTC, West Bank
Hubert H Humphrey Center 25
Enrollment Status:
Closed (57 of 54 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 uses more mathematical notation/delves deeper into theory/application of methods. prereq: [5031 or equiv} or instr consent
Class Notes:
http://classinfo.umn.edu/?jannaj+PA5044+Spring2019
Class Description:
This course is targeted towards students who intend on taking a quantitative approach to policy analysis during graduate school and in their future career. The course will cover the theory behind basic regression models, and illustrate their application in analyzing programs and policies. In order to delve deeply into the assumptions behind such models as well as to understand specific issues that can arise when these assumptions are not met, the course material will use more advanced mathematical notation and concepts, but no calculus is required. Ideally, students entering this course will have a background in economics and/or mathematics/statistics from their undergraduate education. The approach taken to understanding regression analysis in this class will prepare students for more advanced econometrics courses, either offered at the Humphrey school or at other departments in the University.

The syllabus below is from Spring 2016, but Spring 2017's course will be virtually identical. Please see the syllabus for grading and exam information. Contact the instructor with any questions.
Learning Objectives:
This course will cover bivariate and multivariate regression models, including the assumptions behind them and the problems that arise when these assumptions are not met. It covers the same topics as PA5032 (Regression Analysis) but in more depth and using more mathematical notation. Students will also become familiar with the Stata statistical package.
Grading:
45% Assignments (3)
40% Final Exam
15% Class Participation
Class Format:
I teach my lectures from PDF slides. I will try my best to post the day's slides to Moodle by midnight on the day before class. You are welcome to print out the slides and bring them to class to facilitate note-taking.
Textbooks:
https://bookstores.umn.edu/course-lookup/58222/1193
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:
21 February 2017

Spring 2019  |  PA 5044 Section 002: Applied Regression, Accelerated (58223)

Instructor(s)
Class Component:
Laboratory
Times and Locations:
First Half of Term
 
01/22/2019 - 03/11/2019
Fri 09:45AM - 11:00AM
UMTC, West Bank
Hubert H Humphrey Center 85
Auto Enrolls With:
Section 001
Enrollment Status:
Closed (27 of 25 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 uses more mathematical notation/delves deeper into theory/application of methods. prereq: [5031 or equiv} or instr consent
Class Notes:
http://classinfo.umn.edu/?jannaj+PA5044+Spring2019
Class Description:
This course is targeted towards students who intend on taking a quantitative approach to policy analysis during graduate school and in their future career. The course will cover the theory behind basic regression models, and illustrate their application in analyzing programs and policies. In order to delve deeply into the assumptions behind such models as well as to understand specific issues that can arise when these assumptions are not met, the course material will use more advanced mathematical notation and concepts, but no calculus is required. Ideally, students entering this course will have a background in economics and/or mathematics/statistics from their undergraduate education. The approach taken to understanding regression analysis in this class will prepare students for more advanced econometrics courses, either offered at the Humphrey school or at other departments in the University.

The syllabus below is from Spring 2016, but Spring 2017's course will be virtually identical. Please see the syllabus for grading and exam information. Contact the instructor with any questions.
Learning Objectives:
This course will cover bivariate and multivariate regression models, including the assumptions behind them and the problems that arise when these assumptions are not met. It covers the same topics as PA5032 (Regression Analysis) but in more depth and using more mathematical notation. Students will also become familiar with the Stata statistical package.
Grading:
45% Assignments (3)
40% Final Exam
15% Class Participation
Class Format:
I teach my lectures from PDF slides. I will try my best to post the day's slides to Moodle by midnight on the day before class. You are welcome to print out the slides and bring them to class to facilitate note-taking.
Textbooks:
https://bookstores.umn.edu/course-lookup/58223/1193
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:
21 February 2017

Spring 2019  |  PA 5044 Section 003: Applied Regression, Accelerated (58224)

Instructor(s)
Class Component:
Laboratory
Times and Locations:
First Half of Term
 
01/22/2019 - 03/11/2019
Fri 11:15AM - 12:30PM
UMTC, West Bank
Hubert H Humphrey Center 85
Auto Enrolls With:
Section 001
Enrollment Status:
Closed (30 of 29 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 uses more mathematical notation/delves deeper into theory/application of methods. prereq: [5031 or equiv} or instr consent
Class Notes:
http://classinfo.umn.edu/?jannaj+PA5044+Spring2019
Class Description:
This course is targeted towards students who intend on taking a quantitative approach to policy analysis during graduate school and in their future career. The course will cover the theory behind basic regression models, and illustrate their application in analyzing programs and policies. In order to delve deeply into the assumptions behind such models as well as to understand specific issues that can arise when these assumptions are not met, the course material will use more advanced mathematical notation and concepts, but no calculus is required. Ideally, students entering this course will have a background in economics and/or mathematics/statistics from their undergraduate education. The approach taken to understanding regression analysis in this class will prepare students for more advanced econometrics courses, either offered at the Humphrey school or at other departments in the University.

The syllabus below is from Spring 2016, but Spring 2017's course will be virtually identical. Please see the syllabus for grading and exam information. Contact the instructor with any questions.
Learning Objectives:
This course will cover bivariate and multivariate regression models, including the assumptions behind them and the problems that arise when these assumptions are not met. It covers the same topics as PA5032 (Regression Analysis) but in more depth and using more mathematical notation. Students will also become familiar with the Stata statistical package.
Grading:
45% Assignments (3)
40% Final Exam
15% Class Participation
Class Format:
I teach my lectures from PDF slides. I will try my best to post the day's slides to Moodle by midnight on the day before class. You are welcome to print out the slides and bring them to class to facilitate note-taking.
Textbooks:
https://bookstores.umn.edu/course-lookup/58224/1193
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:
21 February 2017

Spring 2018  |  PA 5044 Section 001: Regression Analysis, Accelerated (54888)

Instructor(s)
Class Component:
Lecture
Instructor Consent:
No Special Consent Required
Instruction Mode:
In Person Term Based
Times and Locations:
First Half of Term
 
01/16/2018 - 03/05/2018
Mon, Wed 09:45AM - 11:00AM
UMTC, West Bank
Hubert H Humphrey Center 25
Enrollment Status:
Open (31 of 48 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 uses more mathematical notation/delves deeper into theory/application of methods. prereq: [5031 or equiv} or instr consent
Class Notes:
http://classinfo.umn.edu/?arfertig+PA5044+Spring2018
Class 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 uses more mathematical notation/delves deeper into theory/application of methods. prereq: [5031 or equiv] or instr consent.
NOTE: Required textbook is Introductory Econometrics: A Modern Approach by Jeffrey Wooldridge, most recently published by South-Western College in 2016. However, it is fine if students obtain earlier editions of this book.
Grading:
45% Assignments (3)
40% Final Exam
15% Class Participation
Textbooks:
https://bookstores.umn.edu/course-lookup/54888/1183
Syllabus:
http://classinfo.umn.edu/syllabi/arfertig_PA5044_Spring2018.pdf
Instructor Supplied Information Last Updated:
21 February 2018

Spring 2018  |  PA 5044 Section 002: Regression Analysis, Accelerated (54889)

Instructor(s)
Class Component:
Laboratory
Times and Locations:
First Half of Term
 
01/16/2018 - 03/05/2018
Fri 09:45AM - 11:00AM
UMTC, West Bank
Hubert H Humphrey Center 85
Auto Enrolls With:
Section 001
Enrollment Status:
Closed (31 of 30 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 uses more mathematical notation/delves deeper into theory/application of methods. prereq: [5031 or equiv} or instr consent
Class Notes:
http://classinfo.umn.edu/?arfertig+PA5044+Spring2018
Class 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 uses more mathematical notation/delves deeper into theory/application of methods. prereq: [5031 or equiv] or instr consent.
NOTE: Required textbook is Introductory Econometrics: A Modern Approach by Jeffrey Wooldridge, most recently published by South-Western College in 2016. However, it is fine if students obtain earlier editions of this book.
Grading:
45% Assignments (3)
40% Final Exam
15% Class Participation
Textbooks:
https://bookstores.umn.edu/course-lookup/54889/1183
Syllabus:
http://classinfo.umn.edu/syllabi/arfertig_PA5044_Spring2018.pdf
Instructor Supplied Information Last Updated:
21 February 2018

Spring 2017  |  PA 5044 Section 001: Regression Analysis, Accelerated (55421)

Instructor(s)
Class Component:
Lecture
Instructor Consent:
No Special Consent Required
Instruction Mode:
In Person Term Based
Times and Locations:
First Half of Term
 
01/17/2017 - 03/06/2017
Mon, Wed 09:45AM - 11:00AM
UMTC, West Bank
Carlson School of Management L-122
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 uses more mathematical notation/delves deeper into theory/application of methods. prereq: [5031 or equiv} or instr consent
Class Notes:
http://classinfo.umn.edu/?jannaj+PA5044+Spring2017
Class Description:
This course is targeted towards students who intend on taking a quantitative approach to policy analysis during graduate school and in their future career. The course will cover the theory behind basic regression models, and illustrate their application in analyzing programs and policies. In order to delve deeply into the assumptions behind such models as well as to understand specific issues that can arise when these assumptions are not met, the course material will use more advanced mathematical notation and concepts, but no calculus is required. Ideally, students entering this course will have a background in economics and/or mathematics/statistics from their undergraduate education. The approach taken to understanding regression analysis in this class will prepare students for more advanced econometrics courses, either offered at the Humphrey school or at other departments in the University.

The syllabus below is from Spring 2016, but Spring 2017's course will be virtually identical. Please see the syllabus for grading and exam information. Contact the instructor with any questions.
Learning Objectives:
This course will cover bivariate and multivariate regression models, including the assumptions behind them and the problems that arise when these assumptions are not met. It covers the same topics as PA5032 (Regression Analysis) but in more depth and using more mathematical notation. Students will also become familiar with the Stata statistical package.
Grading:
45% Assignments (3)
40% Final Exam
15% Class Participation
Class Format:
I teach my lectures from PDF slides. I will try my best to post the day's slides to Moodle by midnight on the day before class. You are welcome to print out the slides and bring them to class to facilitate note-taking.
Textbooks:
https://bookstores.umn.edu/course-lookup/55421/1173
Syllabus:
http://classinfo.umn.edu/syllabi/jannaj_PA5044_Spring2017.pdf
Past Syllabi:
http://classinfo.umn.edu/syllabi/jannaj_PA5044_Spring2016.pdf (Spring 2016)
Instructor Supplied Information Last Updated:
21 February 2017

Spring 2017  |  PA 5044 Section 002: Regression Analysis, Accelerated (55422)

Instructor(s)
Class Component:
Laboratory
Times and Locations:
First Half of Term
 
01/17/2017 - 03/06/2017
Fri 09:45AM - 11:00AM
UMTC, West Bank
Hubert H Humphrey Center 85
Auto Enrolls With:
Section 001
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 uses more mathematical notation/delves deeper into theory/application of methods. prereq: [5031 or equiv} or instr consent
Class Notes:
http://classinfo.umn.edu/?jannaj+PA5044+Spring2017
Class Description:
This course is targeted towards students who intend on taking a quantitative approach to policy analysis during graduate school and in their future career. The course will cover the theory behind basic regression models, and illustrate their application in analyzing programs and policies. In order to delve deeply into the assumptions behind such models as well as to understand specific issues that can arise when these assumptions are not met, the course material will use more advanced mathematical notation and concepts, but no calculus is required. Ideally, students entering this course will have a background in economics and/or mathematics/statistics from their undergraduate education. The approach taken to understanding regression analysis in this class will prepare students for more advanced econometrics courses, either offered at the Humphrey school or at other departments in the University.

The syllabus below is from Spring 2016, but Spring 2017's course will be virtually identical. Please see the syllabus for grading and exam information. Contact the instructor with any questions.
Learning Objectives:
This course will cover bivariate and multivariate regression models, including the assumptions behind them and the problems that arise when these assumptions are not met. It covers the same topics as PA5032 (Regression Analysis) but in more depth and using more mathematical notation. Students will also become familiar with the Stata statistical package.
Grading:
45% Assignments (3)
40% Final Exam
15% Class Participation
Class Format:
I teach my lectures from PDF slides. I will try my best to post the day's slides to Moodle by midnight on the day before class. You are welcome to print out the slides and bring them to class to facilitate note-taking.
Textbooks:
https://bookstores.umn.edu/course-lookup/55422/1173
Syllabus:
http://classinfo.umn.edu/syllabi/jannaj_PA5044_Spring2017.pdf
Past Syllabi:
http://classinfo.umn.edu/syllabi/jannaj_PA5044_Spring2016.pdf (Spring 2016)
Instructor Supplied Information Last Updated:
21 February 2017

Spring 2017  |  PA 5044 Section 003: Regression Analysis, Accelerated (55423)

Instructor(s)
Class Component:
Laboratory
Times and Locations:
First Half of Term
 
01/17/2017 - 03/06/2017
Fri 11:15AM - 12:30PM
UMTC, West Bank
Hubert H Humphrey Center 85
Auto Enrolls With:
Section 001
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 uses more mathematical notation/delves deeper into theory/application of methods. prereq: [5031 or equiv} or instr consent
Class Notes:
http://classinfo.umn.edu/?jannaj+PA5044+Spring2017
Class Description:
This course is targeted towards students who intend on taking a quantitative approach to policy analysis during graduate school and in their future career. The course will cover the theory behind basic regression models, and illustrate their application in analyzing programs and policies. In order to delve deeply into the assumptions behind such models as well as to understand specific issues that can arise when these assumptions are not met, the course material will use more advanced mathematical notation and concepts, but no calculus is required. Ideally, students entering this course will have a background in economics and/or mathematics/statistics from their undergraduate education. The approach taken to understanding regression analysis in this class will prepare students for more advanced econometrics courses, either offered at the Humphrey school or at other departments in the University.

The syllabus below is from Spring 2016, but Spring 2017's course will be virtually identical. Please see the syllabus for grading and exam information. Contact the instructor with any questions.
Learning Objectives:
This course will cover bivariate and multivariate regression models, including the assumptions behind them and the problems that arise when these assumptions are not met. It covers the same topics as PA5032 (Regression Analysis) but in more depth and using more mathematical notation. Students will also become familiar with the Stata statistical package.
Grading:
45% Assignments (3)
40% Final Exam
15% Class Participation
Class Format:
I teach my lectures from PDF slides. I will try my best to post the day's slides to Moodle by midnight on the day before class. You are welcome to print out the slides and bring them to class to facilitate note-taking.
Textbooks:
https://bookstores.umn.edu/course-lookup/55423/1173
Syllabus:
http://classinfo.umn.edu/syllabi/jannaj_PA5044_Spring2017.pdf
Past Syllabi:
http://classinfo.umn.edu/syllabi/jannaj_PA5044_Spring2016.pdf (Spring 2016)
Instructor Supplied Information Last Updated:
21 February 2017

Spring 2016  |  PA 5044 Section 001: Regression Analysis, Accelerated (60741)

Instructor(s)
Class Component:
Lecture
Instructor Consent:
No Special Consent Required
Instruction Mode:
In Person Term Based
Times and Locations:
First Half of Term
 
01/19/2016 - 03/07/2016
Mon, Wed 09:45AM - 11:00AM
UMTC, West Bank
Blegen Hall 415
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 PA5032 but uses more mathematical notation/delves deeper into theory/application of methods. prereq: [5031 or equiv}, major or minor in public policy or sci, tech, and environ policy, or PA PhD or instr consent
Class Notes:
http://classinfo.umn.edu/?jannaj+PA5044+Spring2016
Class Description:
This course is targeted towards students who intend on taking a quantitative approach to policy analysis during graduate school and in their future career. The course will cover the theory behind basic regression models, and illustrate their application in analyzing programs and policies. In order to delve deeply into the assumptions behind such models as well as to understand specific issues that can arise when these assumptions are not met, the course material will use more advanced mathematical notation and concepts, but no calculus is required. Ideally, students entering this course will have a background in economics and/or mathematics/statistics from their undergraduate education. The approach taken to understanding regression analysis in this class will prepare students for more advanced econometrics courses, either offered at the Humphrey school or at other departments in the University.

The syllabus below is from Spring 2015, but Spring 2016's course will be virtually identical. Please see the syllabus for grading and exam information. Contact the instructor with any questions.
Textbooks:
https://bookstores.umn.edu/course-lookup/60741/1163
Syllabus:
http://classinfo.umn.edu/syllabi/jannaj_PA5044_Spring2016.pdf
Past Syllabi:
http://classinfo.umn.edu/syllabi/jannaj_PA5044_Spring2017.pdf (Spring 2017)
Instructor Supplied Information Last Updated:
28 October 2015

Spring 2016  |  PA 5044 Section 002: Regression Analysis, Accelerated (60742)

Instructor(s)
Class Component:
Laboratory
Times and Locations:
First Half of Term
 
01/19/2016 - 03/07/2016
Fri 09:45AM - 11:00AM
UMTC, West Bank
Hubert H Humphrey Center 85
Auto Enrolls With:
Section 001
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 PA5032 but uses more mathematical notation/delves deeper into theory/application of methods. prereq: [5031 or equiv}, major or minor in public policy or sci, tech, and environ policy, or PA PhD or instr consent
Class Notes:
http://classinfo.umn.edu/?jannaj+PA5044+Spring2016
Class Description:
This course is targeted towards students who intend on taking a quantitative approach to policy analysis during graduate school and in their future career. The course will cover the theory behind basic regression models, and illustrate their application in analyzing programs and policies. In order to delve deeply into the assumptions behind such models as well as to understand specific issues that can arise when these assumptions are not met, the course material will use more advanced mathematical notation and concepts, but no calculus is required. Ideally, students entering this course will have a background in economics and/or mathematics/statistics from their undergraduate education. The approach taken to understanding regression analysis in this class will prepare students for more advanced econometrics courses, either offered at the Humphrey school or at other departments in the University.

The syllabus below is from Spring 2015, but Spring 2016's course will be virtually identical. Please see the syllabus for grading and exam information. Contact the instructor with any questions.
Textbooks:
https://bookstores.umn.edu/course-lookup/60742/1163
Syllabus:
http://classinfo.umn.edu/syllabi/jannaj_PA5044_Spring2016.pdf
Past Syllabi:
http://classinfo.umn.edu/syllabi/jannaj_PA5044_Spring2017.pdf (Spring 2017)
Instructor Supplied Information Last Updated:
28 October 2015

Spring 2016  |  PA 5044 Section 003: Regression Analysis, Accelerated (60743)

Instructor(s)
Class Component:
Laboratory
Times and Locations:
First Half of Term
 
01/19/2016 - 03/07/2016
Fri 11:15AM - 12:30PM
UMTC, West Bank
Hubert H Humphrey Center 85
Auto Enrolls With:
Section 001
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 PA5032 but uses more mathematical notation/delves deeper into theory/application of methods. prereq: [5031 or equiv}, major or minor in public policy or sci, tech, and environ policy, or PA PhD or instr consent
Class Notes:
http://classinfo.umn.edu/?jannaj+PA5044+Spring2016
Class Description:
This course is targeted towards students who intend on taking a quantitative approach to policy analysis during graduate school and in their future career. The course will cover the theory behind basic regression models, and illustrate their application in analyzing programs and policies. In order to delve deeply into the assumptions behind such models as well as to understand specific issues that can arise when these assumptions are not met, the course material will use more advanced mathematical notation and concepts, but no calculus is required. Ideally, students entering this course will have a background in economics and/or mathematics/statistics from their undergraduate education. The approach taken to understanding regression analysis in this class will prepare students for more advanced econometrics courses, either offered at the Humphrey school or at other departments in the University.

The syllabus below is from Spring 2015, but Spring 2016's course will be virtually identical. Please see the syllabus for grading and exam information. Contact the instructor with any questions.
Textbooks:
https://bookstores.umn.edu/course-lookup/60743/1163
Syllabus:
http://classinfo.umn.edu/syllabi/jannaj_PA5044_Spring2016.pdf
Past Syllabi:
http://classinfo.umn.edu/syllabi/jannaj_PA5044_Spring2017.pdf (Spring 2017)
Instructor Supplied Information Last Updated:
28 October 2015

Spring 2015  |  PA 5044 Section 001: Regression Analysis, Accelerated (68590)

Instructor(s)
Class Component:
Lecture
Instructor Consent:
No Special Consent Required
Instruction Mode:
In Person Term Based
Times and Locations:
First Half of Term
 
01/20/2015 - 03/09/2015
Mon, Wed 09:45AM - 11:00AM
UMTC, West Bank
Carlson School of Management 1-135
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 PA5032 but uses more mathematical notation/delves deeper into theory/application of methods. prereq: Major or minor in public policy or sci, tech, and environ policy, [5031 or equiv or instr consent]
Class Description:
Student may contact the instructor or department for information.
Textbooks:
https://bookstores.umn.edu/course-lookup/68590/1153
Past Syllabi:
http://classinfo.umn.edu/syllabi/jannaj_PA5044_Spring2017.pdf (Spring 2017)
http://classinfo.umn.edu/syllabi/jannaj_PA5044_Spring2016.pdf (Spring 2016)

Spring 2015  |  PA 5044 Section 002: Regression Analysis, Accelerated (68591)

Instructor(s)
Class Component:
Laboratory
Times and Locations:
First Half of Term
 
01/20/2015 - 03/09/2015
Fri 09:45AM - 11:00AM
UMTC, West Bank
Hubert H Humphrey Center 85
Auto Enrolls With:
Section 001
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 PA5032 but uses more mathematical notation/delves deeper into theory/application of methods. prereq: Major or minor in public policy or sci, tech, and environ policy, [5031 or equiv or instr consent]
Class Description:
Student may contact the instructor or department for information.
Textbooks:
https://bookstores.umn.edu/course-lookup/68591/1153
Past Syllabi:
http://classinfo.umn.edu/syllabi/jannaj_PA5044_Spring2017.pdf (Spring 2017)
http://classinfo.umn.edu/syllabi/jannaj_PA5044_Spring2016.pdf (Spring 2016)

Spring 2015  |  PA 5044 Section 003: Regression Analysis, Accelerated (68592)

Instructor(s)
Class Component:
Laboratory
Times and Locations:
First Half of Term
 
01/20/2015 - 03/09/2015
Fri 11:15AM - 12:30PM
UMTC, West Bank
Hubert H Humphrey Center 85
Auto Enrolls With:
Section 001
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 PA5032 but uses more mathematical notation/delves deeper into theory/application of methods. prereq: Major or minor in public policy or sci, tech, and environ policy, [5031 or equiv or instr consent]
Class Description:
Student may contact the instructor or department for information.
Textbooks:
https://bookstores.umn.edu/course-lookup/68592/1153
Past Syllabi:
http://classinfo.umn.edu/syllabi/jannaj_PA5044_Spring2017.pdf (Spring 2017)
http://classinfo.umn.edu/syllabi/jannaj_PA5044_Spring2016.pdf (Spring 2016)

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