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5.0
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5.0
Difficulty
1,000
Ratings given
99%
Would take again
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Search Results
| Name | Grades | Rating | |||
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Not teaching in Spring 2026 | |||||
STAT 7338 Yulia Gel | |||||
A | |||||
Search Results
| Name | Grades | Rating | |||
|---|---|---|---|---|---|
Not teaching in Spring 2026 | |||||
STAT 7338 Yulia Gel | |||||
A | |||||
Yulia Gel
[email protected]Grades: 287
Median GPA: A
Mean GPA: 3.870
4.5
Professor rating
1.7
Difficulty
10
Ratings given
100%
Would take again
Time Series Modeling and Filtering
STAT 7338
School of Natural Sciences and Mathematics
Theory of correlated observations observed sequentially in time. Stationary processes, Autocovariance function. ARMA models. Optimal forecasting in time domain and in frequency domain. Spectral representation. Estimation and model selection. Nonstationary time series models. 3 credit hours.
Prerequisite: STAT 6331.
Offering Frequency: Every two years
Grades: 10
Median GPA: A
Mean GPA: 4.000
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Yulia Gel
[email protected]Grades: 287
Median GPA: A
Mean GPA: 3.870
4.5
Professor rating
1.7
Difficulty
10
Ratings given
100%
Would take again
Time Series Modeling and Filtering
STAT 7338
School of Natural Sciences and Mathematics
Theory of correlated observations observed sequentially in time. Stationary processes, Autocovariance function. ARMA models. Optimal forecasting in time domain and in frequency domain. Spectral representation. Estimation and model selection. Nonstationary time series models. 3 credit hours.
Prerequisite: STAT 6331.
Offering Frequency: Every two years
Grades: 10
Median GPA: A
Mean GPA: 4.000
Click a checkbox to add something to compare.