Lecture notes. Written from the material of Berkeley Stat 153, licensed CC BY 4.0. These are notes, not a transcript: the material has been reorganised and rewritten. This adaptation carries the same licence, and the original is linked above.
128. Supplementary Reading List¶
What this covers¶
This short chapter is not a lecture in the usual sense: it is the course's pointer to the textbooks that sit alongside the lecture notes for the rest of Stat 153. It assumes only that the reader is following the course's own notes and is looking for a fuller treatment of a topic, a second worked example, or a different angle on a method the lecture notes state more tersely.
The two books the course follows most closely¶
The course notes roughly follow chapters from two books, treated as supplements rather than as the primary text:
- Shumway and Stoffer, Time Series Analysis and Its Applications (2017) — available through the UC Berkeley Library.
- Hyndman and Athanasopoulos, Forecasting: Principles and Practice (2021) — freely available online.
Two further references¶
Two additional books on time series are mentioned as optional further reading, at different levels:
- Brockwell and Davis, Introduction to Time Series and Forecasting (2016) — described as the more advanced of the two.
- Cryer and Chan, Time Series Analysis With Applications in R (2008) — described as the more elementary of the two.
Sources¶
docs/statistics/berkeley/stat153/fall-2024/supplementary.md, converted fromsupplementary.qmdin the berkeley-stat153 fall-2024 course repository (commit94c943d), licensed CC BY 4.0. This page is the entire content of that file; no slides, transcript, or exercises were supplied alongside it.
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