3 classes matched your search criteria.

Spring 2022  |  ECON 4261 Section 001: Introduction to Econometrics (53830)

Instructor(s)
Class Component:
Lecture
Instructor Consent:
No Special Consent Required
Instruction Mode:
In Person Term Based
Enrollment Requirements:
Economics BS major
Times and Locations:
Regular Academic Session
 
01/18/2022 - 05/02/2022
Tue, Thu 08:15AM - 09:15AM
UMTC, West Bank
Anderson Hall 230
Enrollment Status:
Open (49 of 80 seats filled)
Also Offered:
Course Catalog Description:
For Econ B.S. majors only. Review of basic linear regression model, its variants. Time series/simultaneous equation models. Material may include panel data, censored/truncated regressions, discrete choice models. prereq: [3101 or equiv], [[Math 1271, Math 1272] or equiv], Math 2243, Math 2263, [[Stat 4101, Stat 4102] or [Stat 5101, Stat 5102]]; Math 4242 strongly recommended
Class Description:
This is a required course for Economics B.S. majors. Students must have completed all prerequisites successfully PRIOR to taking this course. The course includes the basic linear regression model, time series analysis, panel data, discrete choice models. Computer applications (normally GAUSS is used).
Exam Format:
problems
Class Format:
75% Lecture
25% Other Style Recitation discussion
Workload:
40-50 Pages Reading Per Week
2 Exam(s)
Textbooks:
https://bookstores.umn.edu/course-lookup/53830/1223
Instructor Supplied Information Last Updated:
4 September 2007

Spring 2022  |  ECON 4261 Section 002: Introduction to Econometrics (53831)

Instructor(s)
Class Component:
Discussion
Times and Locations:
Regular Academic Session
 
01/18/2022 - 05/02/2022
Thu 12:20PM - 01:10PM
UMTC, West Bank
Blegen Hall 220
Auto Enrolls With:
Section 001
Enrollment Status:
Open (36 of 40 seats filled)
Course Catalog Description:
For Econ B.S. majors only. Review of basic linear regression model, its variants. Time series/simultaneous equation models. Material may include panel data, censored/truncated regressions, discrete choice models. prereq: [3101 or equiv], [[Math 1271, Math 1272] or equiv], Math 2243, Math 2263, [[Stat 4101, Stat 4102] or [Stat 5101, Stat 5102]]; Math 4242 strongly recommended
Class Description:
This is a required course for Economics B.S. majors. Students must have completed all prerequisites successfully PRIOR to taking this course. The course includes the basic linear regression model, time series analysis, panel data, discrete choice models. Computer applications (normally GAUSS is used).
Exam Format:
problems
Class Format:
75% Lecture
25% Other Style Recitation discussion
Workload:
40-50 Pages Reading Per Week
2 Exam(s)
Textbooks:
https://bookstores.umn.edu/course-lookup/53831/1223
Instructor Supplied Information Last Updated:
4 September 2007

Spring 2022  |  ECON 4261 Section 004: Introduction to Econometrics (54563)

Instructor(s)
Class Component:
Discussion
Times and Locations:
Regular Academic Session
 
01/18/2022 - 05/02/2022
Thu 01:25PM - 02:15PM
UMTC, West Bank
Blegen Hall 220
Auto Enrolls With:
Section 001
Enrollment Status:
Open (13 of 40 seats filled)
Course Catalog Description:
For Econ B.S. majors only. Review of basic linear regression model, its variants. Time series/simultaneous equation models. Material may include panel data, censored/truncated regressions, discrete choice models. prereq: [3101 or equiv], [[Math 1271, Math 1272] or equiv], Math 2243, Math 2263, [[Stat 4101, Stat 4102] or [Stat 5101, Stat 5102]]; Math 4242 strongly recommended
Class Description:
This is a required course for Economics B.S. majors. Students must have completed all prerequisites successfully PRIOR to taking this course. The course includes the basic linear regression model, time series analysis, panel data, discrete choice models. Computer applications (normally GAUSS is used).
Exam Format:
problems
Class Format:
75% Lecture
25% Other Style Recitation discussion
Workload:
40-50 Pages Reading Per Week
2 Exam(s)
Textbooks:
https://bookstores.umn.edu/course-lookup/54563/1223
Instructor Supplied Information Last Updated:
4 September 2007

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