13 classes matched your search criteria.

PA 5044 is also offered in Spring 2019

PA 5044 is also offered in Spring 2018

PA 5044 is also offered in Spring 2017

PA 5044 is also offered in Spring 2016

PA 5044 is also offered in Spring 2015

## Spring 2019 | PA 5044 Section 001: Regression Analysis, 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 Bank
- 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:
- http://www.bookstores.umn.edu/buybooks.cgi?deptlookup=1&search=PA5044~001&term=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: Regression Analysis, Accelerated (58223)

- Instructor(s)
- Class Component:
- Laboratory
- Times and Locations:
- First Half of Term01/22/2019 - 03/11/2019Fri 09:45AM - 11:00AMUMTC, West Bank
- 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+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:
- http://www.bookstores.umn.edu/buybooks.cgi?deptlookup=1&search=PA5044~002&term=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
- 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.
- Textbooks:
- http://www.bookstores.umn.edu/buybooks.cgi?deptlookup=1&search=PA5044~001&term=1183
- Instructor Supplied Information Last Updated:
- 2 November 2017

## 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

- Course Catalog Description:
- 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.
- Textbooks:
- http://www.bookstores.umn.edu/buybooks.cgi?deptlookup=1&search=PA5044~002&term=1183
- Instructor Supplied Information Last Updated:
- 2 November 2017

## 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:
- 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:
- http://www.bookstores.umn.edu/buybooks.cgi?deptlookup=1&search=PA5044~001&term=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:
- 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.
- Learning Objectives:
- Grading:
- 45% Assignments (3)

40% Final Exam

15% Class Participation - Class Format:
- Textbooks:
- http://www.bookstores.umn.edu/buybooks.cgi?deptlookup=1&search=PA5044~002&term=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:
- 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.
- Learning Objectives:
- Grading:
- 45% Assignments (3)

40% Final Exam

15% Class Participation - Class Format:
- Textbooks:
- http://www.bookstores.umn.edu/buybooks.cgi?deptlookup=1&search=PA5044~003&term=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:
- http://www.bookstores.umn.edu/buybooks.cgi?deptlookup=1&search=PA5044~001&term=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:
- http://www.bookstores.umn.edu/buybooks.cgi?deptlookup=1&search=PA5044~002&term=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:
- http://www.bookstores.umn.edu/buybooks.cgi?deptlookup=1&search=PA5044~003&term=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:
- http://www.bookstores.umn.edu/buybooks.cgi?deptlookup=1&search=PA5044~001&term=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:
- http://www.bookstores.umn.edu/buybooks.cgi?deptlookup=1&search=PA5044~002&term=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:
- http://www.bookstores.umn.edu/buybooks.cgi?deptlookup=1&search=PA5044~003&term=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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