Fall 2019 - STAT 485 E100
Applied Time Series Analysis (3)
Class Number: 4585
Delivery Method: In Person
Course Times + Location:
Mo 5:30 PM – 6:20 PM
AQ 3182, Burnaby
Th 4:30 PM – 6:20 PM
EDB 7618, Burnaby
Exam Times + Location:
Dec 6, 2019
7:00 PM – 10:00 PM
SSCB 9201, Burnaby
Prerequisites:STAT 285 or STAT 302 or STAT 305 or BUEC 333 or equivalent.
Introduction to linear time series analysis including moving average, autoregressive and ARIMA models, estimation, data analysis, forecasting errors and confidence intervals, conditional and unconditional models, and seasonal models. This course may not be taken for further credit by students who have credit for ECON 484. Quantitative.
- Autocorrelation, seasonality, and trends in time series and their impacts on standard statistical inference techniques.
- Autoregressive models: definition, model formulation, and data analysis
- Moving average models: definition model formulation, and data analysis
- ARIMA models: definition, model formulation, and data analysis
- Introduction to forecasting with linear time series models
- Introduction to nonparametric fitting of trends and cycles to time series data
- Assignments 10%
- Midterm 1 25%
- Midterm 2 25%
- Final 40%
Above grading is subject to change.
Time Series Analysis with Applications in R (2nd ed.) by Jonathan D. Cryer and Kung-Sik Chan. Publisher: Springer
- Book is available on-line for free through the SFU Libarary
Hardcover ISBN: 978-0-387-75958-6
Softcover ISBN: 978-1-4419-2613-5
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