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5.0
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5.0
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1,000
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99%
Would take again
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| Name | Grades | Rating | |||
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Not teaching in Spring 2026 | |||||
ECON 6306 Daniel O'Brien | |||||
A | |||||
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| Name | Grades | Rating | |||
|---|---|---|---|---|---|
Not teaching in Spring 2026 | |||||
ECON 6306 Daniel O'Brien | |||||
A | |||||
Daniel O'Brien
[email protected]Grades: 451
Median GPA: A
Mean GPA: 3.707
4.4
Professor rating
2.1
Difficulty
15
Ratings given
90%
Would take again
Applied Econometrics
ECON 6306
School of Economic, Political and Policy Sciences
This course investigates the consequences of relaxing the classical linear regression model assumptions and explores solutions when the assumptions do not hold. Topics include a review of the Ordinary Least Squares (OLS) basics (including the assumptions, hypothesis testing, multicolinearity, dummy variables and heteroskedasticity), model specification and selection, Generalized Least Squares (GLS), maximum likelihood estimation, binary choice models, simultaneous equation models, instrumental variables, time series and fixed and random effects models. 3 credit hours.
Offering Frequency: Each year
Grades: 307
Median GPA: A
Mean GPA: 3.719
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Daniel O'Brien
[email protected]Grades: 451
Median GPA: A
Mean GPA: 3.707
4.4
Professor rating
2.1
Difficulty
15
Ratings given
90%
Would take again
Applied Econometrics
ECON 6306
School of Economic, Political and Policy Sciences
This course investigates the consequences of relaxing the classical linear regression model assumptions and explores solutions when the assumptions do not hold. Topics include a review of the Ordinary Least Squares (OLS) basics (including the assumptions, hypothesis testing, multicolinearity, dummy variables and heteroskedasticity), model specification and selection, Generalized Least Squares (GLS), maximum likelihood estimation, binary choice models, simultaneous equation models, instrumental variables, time series and fixed and random effects models. 3 credit hours.
Offering Frequency: Each year
Grades: 307
Median GPA: A
Mean GPA: 3.719
Click a checkbox to add something to compare.