STAT 223: Time Series Analysis
University of California, Santa Cruz
Graduate level introductory course on time series data and models in the time and frequency domains: descriptive time series methods; the periodogram; basic theory of stationary processes; linear filters; spectral analysis; time series analysis for repeated measurements; ARIMA models; introduction to Bayesian spectral analysis; Bayesian learning, forecasting, and smoothing; introduction to Bayesian Dynamic Linear Models (DLMs); DLM mathematical structure; DLMs for trends and seasonal patterns; and autoregression and time series regression models. (Formerly AMS 223.)
Average GPA: 3.73
Grade distribution records: 21 students across 2 terms.
Grade distribution
| Grade | Students | Percent |
|---|---|---|
| A+ | 3 | 14.3% |
| A | 1 | 4.8% |
| A- | 1 | 4.8% |
| B- | 1 | 4.8% |
| S | 15 | 71.4% |
Based on 21 student grade records across 2 terms and 2 professors.
Instructors
- Raquel Prado 11 students, Average GPA 4.00
- Rebecca Killick 10 students, Average GPA 3.60