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STAT 464 Discrete Time Series Analysis Units: 3.00
Autocorrelation and autocovariance, stationarity; ARIMA models; model identification and forecasting; spectral analysis. Applications to biological, physical and economic data.
Learning Hours: 120 (36 Lecture, 84 Private Study)
Offering Faculty: Faculty of Arts and Science
Course Learning Outcomes:
- Deal with deterministic temporal structure in the data collected.
- Use time-series models to do forecasting
- Work with probabilistic analysis of regular time-series data.
- Work with time-series data collected at regular intervals over time, e.g., daily temperature.