3 classes matched your search criteria.

Spring 2022  |  PA 5033 Section 004: Multivariate Techniques (58910)

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:
Second Half of Term
 
03/15/2022 - 05/02/2022
Mon, Wed 09:45AM - 11:00AM
UMTC, West Bank
Enrollment Status:
Open (0 of 48 seats filled)
Also Offered:
Course Catalog Description:
Use of bivariate and multivariate statistical approaches for analyzing and evaluating public affairs issues and the assumptions behind the analytical approaches. Designed to help students read, understand, interpret, use, and evaluate empirical work used in social sciences by policy analysts and policy makers. prereq: [5032 or 5044 or equiv] or instr consent. May fulfill stats requirements in other programs.
Class Notes:
http://classinfo.umn.edu/?klein002+PA5033+Spring2021
Class Description:
This class examines how statistical approaches can be used to examine public policies. This course is designed to help the student read, understand, interpret, use and evaluate empirical work used in the social sciences and by policy analysts. The course concentrates attention on several quantitative techniques used by public policy researchers and advisors to policy makers. The course covers techniques such as time series analysis, statistical cause and effect, forecasting models, limited dependent variables, combining time series and cross section data, and an introduction to big data and machine learning. A basic statistics class is a required prerequisite. Here is a link to a video: http://player.vimeo.com/external/89316179.sd.mp4?s=5148a78bbdba654e8040327fa8ae93f1
Who Should Take This Class?:

To learn quantitative techniques such as time series analysis, statistical cause and effect, forecasting models, limited dependent variables, combining time series and cross section data, and an introduction to big data and machine learning.

https://bookstores.umn.edu/course-lookup/58910/1223

Past Syllabi:
http://classinfo.umn.edu/syllabi/klein002_PA5033_Spring2021.doc (Spring 2021)
http://classinfo.umn.edu/syllabi/klein002_PA5033_Spring2019.doc (Spring 2019)
Instructor Supplied Information Last Updated:
10 December 2020

Spring 2022  |  PA 5033 Section 005: Multivariate Techniques (58911)

Instructor(s)
Class Component:
Laboratory
Times and Locations:
Second Half of Term
 
03/15/2022 - 05/02/2022
Fri 01:50PM - 02:40PM
UMTC, West Bank
Hubert H Humphrey Center 85
Auto Enrolls With:
Section 004
Enrollment Status:
Open (0 of 24 seats filled)
Course Catalog Description:
Use of bivariate and multivariate statistical approaches for analyzing and evaluating public affairs issues and the assumptions behind the analytical approaches. Designed to help students read, understand, interpret, use, and evaluate empirical work used in social sciences by policy analysts and policy makers. prereq: [5032 or 5044 or equiv] or instr consent. May fulfill stats requirements in other programs.
Class Notes:
http://classinfo.umn.edu/?klein002+PA5033+Spring2021
Class Description:
This class examines how statistical approaches can be used to examine public policies. This course is designed to help the student read, understand, interpret, use and evaluate empirical work used in the social sciences and by policy analysts. The course concentrates attention on several quantitative techniques used by public policy researchers and advisors to policy makers. The course covers techniques such as time series analysis, statistical cause and effect, forecasting models, limited dependent variables, combining time series and cross section data, and an introduction to big data and machine learning. A basic statistics class is a required prerequisite. Here is a link to a video: http://player.vimeo.com/external/89316179.sd.mp4?s=5148a78bbdba654e8040327fa8ae93f1
Who Should Take This Class?:

To learn quantitative techniques such as time series analysis, statistical cause and effect, forecasting models, limited dependent variables, combining time series and cross section data, and an introduction to big data and machine learning.

https://bookstores.umn.edu/course-lookup/58911/1223

Past Syllabi:
http://classinfo.umn.edu/syllabi/klein002_PA5033_Spring2021.doc (Spring 2021)
http://classinfo.umn.edu/syllabi/klein002_PA5033_Spring2019.doc (Spring 2019)
Instructor Supplied Information Last Updated:
10 December 2020

Spring 2022  |  PA 5033 Section 006: Multivariate Techniques (58914)

Instructor(s)
Class Component:
Laboratory
Times and Locations:
Second Half of Term
 
03/15/2022 - 05/02/2022
Fri 12:45PM - 01:35PM
UMTC, West Bank
Hubert H Humphrey Center 85
Auto Enrolls With:
Section 004
Enrollment Status:
Open (0 of 24 seats filled)
Course Catalog Description:
Use of bivariate and multivariate statistical approaches for analyzing and evaluating public affairs issues and the assumptions behind the analytical approaches. Designed to help students read, understand, interpret, use, and evaluate empirical work used in social sciences by policy analysts and policy makers. prereq: [5032 or 5044 or equiv] or instr consent. May fulfill stats requirements in other programs.
Class Notes:
http://classinfo.umn.edu/?klein002+PA5033+Spring2021
Class Description:
This class examines how statistical approaches can be used to examine public policies. This course is designed to help the student read, understand, interpret, use and evaluate empirical work used in the social sciences and by policy analysts. The course concentrates attention on several quantitative techniques used by public policy researchers and advisors to policy makers. The course covers techniques such as time series analysis, statistical cause and effect, forecasting models, limited dependent variables, combining time series and cross section data, and an introduction to big data and machine learning. A basic statistics class is a required prerequisite. Here is a link to a video: http://player.vimeo.com/external/89316179.sd.mp4?s=5148a78bbdba654e8040327fa8ae93f1
Who Should Take This Class?:

To learn quantitative techniques such as time series analysis, statistical cause and effect, forecasting models, limited dependent variables, combining time series and cross section data, and an introduction to big data and machine learning.

https://bookstores.umn.edu/course-lookup/58914/1223

Past Syllabi:
http://classinfo.umn.edu/syllabi/klein002_PA5033_Spring2021.doc (Spring 2021)
http://classinfo.umn.edu/syllabi/klein002_PA5033_Spring2019.doc (Spring 2019)
Instructor Supplied Information Last Updated:
10 December 2020

ClassInfo Links - Spring 2022 5000 Level Public Affairs Classes Taught by Morris Kleiner

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