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Search Results
| Name | Grades | Rating | |||
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Not teaching in Spring 2026 | |||||
EPPS 7370 (Overall) | |||||
A- | |||||
EPPS 7370 Patrick Brandt | |||||
A- | |||||
Search Results
| Name | Grades | Rating | |||
|---|---|---|---|---|---|
Not teaching in Spring 2026 | |||||
EPPS 7370 (Overall) | |||||
A- | |||||
EPPS 7370 Patrick Brandt | |||||
A- | |||||
Time Series Analysis I
EPPS 7370
School of Economic, Political and Policy Sciences
This course considers several important topics for applied time series analyses of social science and public policy data including the specification and testing of Box-Jenkins ARIMA models and dynamic regressions. Other topics include stationarity and unit root tests, cointegration and error correction models, autoregressive conditional heterogeneity (GARCH) models and introductions to vector autoregression (VAR) and state space models. Students learn how to use modern software such as Eviews, R, RATS and Stata to do time series analyses. Recommended: EPPS 7316 or equivalent. 3 credit hours.
Offering Frequency: Every two years
Grades: 57
Median GPA: A-
Mean GPA: 3.613
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Time Series Analysis I
EPPS 7370
School of Economic, Political and Policy Sciences
This course considers several important topics for applied time series analyses of social science and public policy data including the specification and testing of Box-Jenkins ARIMA models and dynamic regressions. Other topics include stationarity and unit root tests, cointegration and error correction models, autoregressive conditional heterogeneity (GARCH) models and introductions to vector autoregression (VAR) and state space models. Students learn how to use modern software such as Eviews, R, RATS and Stata to do time series analyses. Recommended: EPPS 7316 or equivalent. 3 credit hours.
Offering Frequency: Every two years
Grades: 57
Median GPA: A-
Mean GPA: 3.613
Click a checkbox to add something to compare.