3 classes matched your search criteria.
PA 5044 is also offered in Spring 2023
PA 5044 is also offered in Spring 2022
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
ClassInfo Links - Spring 2017 Public Affairs Classes
- To link directly to this ClassInfo page from your website or to save it as a bookmark, use:
- http://classinfo.umn.edu/?subject=PA&catalog_nbr=5044&term=1173
- To see a URL-only list for use in the Faculty Center URL fields, use:
- http://classinfo.umn.edu/?subject=PA&catalog_nbr=5044&term=1173&url=1
- To see this page output as XML, use:
- http://classinfo.umn.edu/?subject=PA&catalog_nbr=5044&term=1173&xml=1
- To see this page output as JSON, use:
- http://classinfo.umn.edu/?subject=PA&catalog_nbr=5044&term=1173&json=1
- To see this page output as CSV, use:
- http://classinfo.umn.edu/?subject=PA&catalog_nbr=5044&term=1173&csv=1
ClassInfo created and maintained by the Humphrey School of Public Affairs.
If you have questions about specific courses, we strongly encourage you to contact the department where the course resides.