What we’re about
Time Series Lab: Theory & Practice is a discussion-driven learning group for people who work with or are curious about temporal data and want to understand it beyond running black-box models. We alternate between theory-focused sessions (foundations like stationarity, state-space models, Bayesian and causal time series) and applied sessions (real-world papers, case studies, and datasets from domains like healthcare, product analytics, finance, and sensors). The emphasis is on assumptions, modeling choices, and failure modes—what works, what breaks, and why.
Upcoming events
1
Time Series Lab — Session 1
Online, NA, San Francisco, CA, USTime Series Lab - Session 1
Introduction + Chapter 1 of Time Series Analysis and Its Applications (Shumway & Stoffer)
This is the kickoff event for the Time Series Lab: Theory ↔ Practice.
In this first session, we’ll briefly introduce the group’s structure and goals, then dive into Chapter 1 of Time Series Analysis and Its Applications by Shumway & Stoffer. This chapter sets the foundation for everything that follows: what makes time series data different, examples of temporal dependence, and why classical IID assumptions fail when data evolves over time.
No prior time-series expertise is required. Familiarity with basic probability and linear algebra is helpful, but the focus will be on intuition, concepts, and discussion rather than heavy derivations.
📘 Reading (Optional but Encouraged)
- Time Series Analysis and Its Applications, Chapter 1
(We’ll summarize key points during the session.)
🗂 Tentative Agenda
- 10 min — Introductions & overview of the group
- 25 min — Walk-through of Chapter 1 (key ideas & intuition)
- 25 min — Discussion: temporal dependence, examples from real work, and open questions
Slack channel.
4 attendees- Time Series Analysis and Its Applications, Chapter 1
Group links
Organizers
Members
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