Fall 2021  |  POL 8108 Section 001: Maximum Likelihood Estimation (22425)

Instructor(s)
Class Component:
Laboratory
Credits:
3 Credits
Grading Basis:
Student Option
Instructor Consent:
No Special Consent Required
Instruction Mode:
In Person Term Based
Enrollment Requirements:
Pol Sci grad major
Times and Locations:
Regular Academic Session
 
09/07/2021 - 12/15/2021
Wed 09:00AM - 10:55AM
UMTC, West Bank
Social Sciences Building 1383
Enrollment Status:
Open (3 of 10 seats filled)
Also Offered:
Course Catalog Description:
This course presents an overview of the likelihood theory of statistical inference, and its wide range of uses in applied quantitative political science. When dependent variables take the form of ordered or unordered categories, event counts, or otherwise violate the traditional assumptions of the linear regression model, models estimated by maximum likelihood provide an essential alternative. Topics covered include binary, multinomial, and ordered logit/probit, Poisson regression, and multilevel models. We will rely heavily on computational methods of analysis using the R statistical computing environment, and instruction on how to use R for applied research will be provided throughout the length of the course.
Class Description:
Student may contact the instructor or department for information.
Textbooks:
https://bookstores.umn.edu/course-lookup/22425/1219

ClassInfo Links - Fall 2021 Political Science Classes

To link directly to this ClassInfo page from your website or to save it as a bookmark, use:
http://classinfo.umn.edu/?subject=POL&catalog_nbr=8108&term=1219
To see a URL-only list for use in the Faculty Center URL fields, use:
http://classinfo.umn.edu/?subject=POL&catalog_nbr=8108&term=1219&url=1
To see this page output as XML, use:
http://classinfo.umn.edu/?subject=POL&catalog_nbr=8108&term=1219&xml=1
To see this page output as JSON, use:
http://classinfo.umn.edu/?subject=POL&catalog_nbr=8108&term=1219&json=1
To see this page output as CSV, use:
http://classinfo.umn.edu/?subject=POL&catalog_nbr=8108&term=1219&csv=1
Schedule Viewer
8 am
9 am
10 am
11 am
12 pm
1 pm
2 pm
3 pm
4 pm
5 pm
6 pm
7 pm
8 pm
9 pm
10 pm
s
m
t
w
t
f
s
?
Class Title