# Statistics 153: Introduction to Time Series

UC Berkeley, Fall 2024

**Instructor:**Ryan Tibshirani (ryantibs at berkeley dot edu)**GSI:**Tiffany Ding (tiffany_ding at berkeley dot edu)**Reader:**Theo Pan (theopan at berkeley dot edu)

*Please email the GSI with any issues; the Instructor will be looped in only as-needed.*

**Class times:**Tuesdays and Thursdays, 2-3:30pm, McCone 141**Lab times:**Fridays, 9-11am, Evans 344 and 1-3pm, Evans 334**Office hours:**RT: Thursdays, 1-2pm, Evans 417

Make sure to read the syllabus. Other handy links:

- GitHub repo (source files for lectures and homeworks)
- Ed Discussion (for class discussions and announcements)
- bCourses (for grade-keeping and homework solutions)

### Schedule

Week 1: Aug 29 | Characteristics of time series: pdf, html, source | |

Week 2: Sep 3-5 | Measures of dependence: pdf, html, source | |

Week 3: Sep 10-12 | Regression and prediction: pdf, html, source | Hw 1 due Fri Sep 13 |

Week 4: Sep 17-19 | Regression and prediction (continued) | |

Week 5: Sep 24-26 | Regularization and smoothing: pdf, html, source | Hw 2 due Fri Sep 27 |

Week 6: Oct 1-3 | Regularization and smoothing (continued) | |

Week 7: Oct 8-10 | Spectral analysis: pdf, html, source | Hw 3 due Fri Oct 11 |

Week 8: Oct 15-17 | Spectral analysis (continued) | |

Week 9: Oct 22-24 | ARIMA models: pdf, html, source | Midterm on Oct 21 |

Week 10: Oct 29-31 | ARIMA models (continued) | |

Week 11: Nov 5-7 | ETS models: pdf, html, source | Hw 4 due Fri Nov 8 |

Week 12: Nov 12-14 | ETS models (continued on Tues; canceled on Thurs for BSTARS) | |

Week 13: Nov 19-21 | Advanced topics: pdf, html, source | Hw 5 due Fri Nov 22 |

Week 14: Nov 26-28 | (Nothing! Enjoy Thanksgiving) | |

Week 15: Dec 3-5 | Advanced topics (continued) | Final exam TBD |

### Homework

### Supplementary resources

We will (roughly) follow some chapters of the following two books, which you can look at as supplements to the lecture notes. The first should be available to you by searching for it online through the UC Berkeley Library, and the second is freely available at the link below.

- Shumway, Stoffer, Time Series Analysis and Its Applications, 2017.
- Hyndman, Athanasopoulos, Forecasting: Principles and Practice, 2021.

Below are two other references on time series that may be helpful as well. The first is more advanced, and the second more elementary.

- Brockwell, David, Introduction to Time Series and Forecasting, 2016.
- Cryer, Chan, Time Series Analysis With Applications in R, 2008.

This work is licensed under a Creative Commons Attribution 4.0 International License.