23 classes matched your search criteria.
PA 5044 is also offered in Spring 2023
PA 5044 is also offered in Spring 2022
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 Term01/17/2023 - 03/13/2023Mon, Wed 09:45AM - 11:00AMUMTC, West BankBlegen 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 Term01/17/2023 - 03/13/2023Fri 09:45AM - 11:00AMUMTC, West BankHubert 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 Term01/17/2023 - 03/13/2023Fri 11:15AM - 12:30PMUMTC, West BankHubert 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 Term01/18/2022 - 03/14/2022Mon, Wed 09:45AM - 11:00AMUMTC, West BankBlegen 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 Term01/18/2022 - 03/14/2022Fri 09:45AM - 11:00AMUMTC, West BankHubert 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 Term01/18/2022 - 03/14/2022Fri 11:15AM - 12:30PMUMTC, West BankHubert 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 Term01/21/2020 - 03/16/2020Mon, Wed 09:45AM - 11:00AMUMTC, West BankHubert 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 Term01/21/2020 - 03/16/2020Fri 09:45AM - 11:00AMUMTC, West BankHubert 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 Term01/21/2020 - 03/16/2020Fri 11:15AM - 12:30PMUMTC, West BankHubert 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 Term01/22/2019 - 03/11/2019Mon, Wed 09:45AM - 11:00AMUMTC, West BankHubert 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 Term01/22/2019 - 03/11/2019Fri 09:45AM - 11:00AMUMTC, West BankHubert 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 Term01/22/2019 - 03/11/2019Fri 11:15AM - 12:30PMUMTC, West BankHubert 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 Term01/16/2018 - 03/05/2018Mon, Wed 09:45AM - 11:00AMUMTC, West BankHubert 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 Exam15% 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 Term01/16/2018 - 03/05/2018Fri 09:45AM - 11:00AMUMTC, West BankHubert 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 Exam15% 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 Term01/17/2017 - 03/06/2017Mon, Wed 09:45AM - 11:00AMUMTC, West BankCarlson 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 Term01/17/2017 - 03/06/2017Fri 09:45AM - 11:00AMUMTC, West BankHubert 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 Term01/17/2017 - 03/06/2017Fri 11:15AM - 12:30PMUMTC, West BankHubert 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 Term01/19/2016 - 03/07/2016Mon, Wed 09:45AM - 11:00AMUMTC, West BankBlegen 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 Term01/19/2016 - 03/07/2016Fri 09:45AM - 11:00AMUMTC, West BankHubert 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 Term01/19/2016 - 03/07/2016Fri 11:15AM - 12:30PMUMTC, West BankHubert 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 Term01/20/2015 - 03/09/2015Mon, Wed 09:45AM - 11:00AMUMTC, West BankCarlson 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 Term01/20/2015 - 03/09/2015Fri 09:45AM - 11:00AMUMTC, West BankHubert 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 Term01/20/2015 - 03/09/2015Fri 11:15AM - 12:30PMUMTC, West BankHubert 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)
ClassInfo Links - Public Affairs Classes
- To link directly to this ClassInfo page from your website or to save it as a bookmark, use:
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- http://classinfo.umn.edu/?subject=PA&catalog_nbr=5044&url=1
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- http://classinfo.umn.edu/?subject=PA&catalog_nbr=5044&xml=1
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If you have questions about specific courses, we strongly encourage you to contact the department where the course resides.