SDS 4155 / SDS 5155 Time Series Analysis

Course description

This senior-level course develops the statistical ideas and practical tools used to analyze data observed over time. We begin with data integrity, exploratory analysis, and the transition from general nonstationary series to useful stationary representations. The core of the course covers autocorrelation, stationary processes, ARMA and ARIMA models, estimation, diagnostics, and forecasting. Later topics include seasonal models, dynamic regression, exponential smoothing, state-space methods, spectral analysis, volatility, change points, multivariate series, and a nontechnical survey of modern forecasting methods. Mathematical ideas are stated carefully, but the emphasis is on interpretation, model-building decisions, reproducible computation, and examples drawn from real data.

Prerequisites and materials

Prerequisites

Math 493 (Probability) and Math 494 (Mathematical Statistics), or permission of the instructor. Familiarity with regression is expected; prior experience with R is helpful but not required.

Textbook

Robert H. Shumway and David S. Stoffer, Time Series Analysis and Its Applications: With R Examples, 4th ed., Springer, 2017. Assigned readings and most formal notation will follow this text; supplementary notes will be used for data cleaning and selected modern topics.

Software

We will use the open-source statistical software R and, optionally, RStudio Desktop. Required code, data, and reproducible examples will be distributed through Canvas or the course site.

Coursework and exams

Homework

Homework will normally be assigned weekly during teaching weeks. Assignments will combine short derivations, interpretation, data analysis, and reproducible R work. Unless an assignment states otherwise, homework is due Wednesday at 11:59 p.m. Central Time. Solutions or model analyses will be posted after submission closes, and students should document data checks, assumptions, model choices, diagnostics, and conclusions.

Routine late submissions are not accepted after solutions are released. Students with an approved accommodation or a documented emergency should contact the instructor as soon as possible.

Exams

There will be one in-class midterm and one cumulative final. Exams are closed book and closed notes, except for one letter-size sheet of notes written on both sides. Calculators are allowed; internet access and statistical software are not permitted unless different instructions are announced in writing.

• Midterm: Tuesday, October 13, 2026, 10:00–11:20 a.m., MCMILLIN X, Room 0G052.
• Final exam: university final-exam period, December 10–16; exact assignment to be announced by the registrar.

Make-up exams are reserved for documented conflicts, university-approved accommodations, or emergencies. Notify the instructor before the exam whenever possible; in an emergency, make contact promptly and provide documentation within two business days. A make-up will ordinarily be completed within one week of the scheduled exam.

Grading

Letter-grade thresholds: A ≥ 92; A− 90–<92; B+ 88–<90; B 82–<88; B− 80–<82; C+ 78–<80; C 72–<78; C− 70–<72; D+ 68–<70; D 62–<68; D− 60–<62; F < 60.

An A+ may be awarded for exceptional performance. Course scores will be compared with these fixed thresholds without individual rounding or grade adjustments. Any clarification to the grading scale will be announced in writing and applied consistently to the entire class.

Course policies and student support

Collaboration, academic integrity, and AI

Students may discuss concepts and general approaches on homework, but each student must write and submit their own analysis, explanations, and code and must acknowledge substantive help. Unless an assignment explicitly permits it, generative AI may not be used to produce or substantially revise work submitted for credit. Exams must be completed independently using only the materials authorized for that exam. All work is subject to Washington University’s Academic Integrity Policy.

Accessibility and accommodations

Students seeking disability-related accommodations should work with Disability Resources and share their accommodation letter with the instructor. Please arrange a conversation early so that approved accommodations, including exam arrangements, can be implemented effectively.

Religious observance and other university-approved absences

Notify the instructor in writing as early as possible—ideally by the end of the third week of class—about a religious observance or other university-approved absence that conflicts with coursework or an exam. Reasonable arrangements will be made without academic penalty.

Learning and well-being

Students may consult the university’s Campus Resources page for Disability Resources, the Learning Center, the Writing Center & Speaking Studio, and well-being support. If circumstances are affecting your work, contact the instructor early so available options can be discussed.

Changes to this syllabus

The instructor may adjust the topic sequence, homework pacing, or other details to support learning. University holidays and the announced midterm date are fixed; any other change will be announced in Canvas and reflected on the course schedule.