Course: STAT 26100=STAT 33600
Title: Time Dependent Data
Instructor(s): Wei Biao Wu
Teaching Assistant(s): Wanrong Zhu
Class Schedule: Sec 01: TR 9:40 AM–11:00 AM in TBA
Textbook(s): Shumay, Stoffer, Time Series Analysis and Its Applications with R Examples, 3rd edition. Available online on any UChicago network.
Description: This course considers the modeling and analysis of data that are ordered in time. The main focus is on quantitative observations taken at evenly spaced intervals and includes both time-domain and spectral approaches.
Prerequisites: STAT 24500 w/B- or better or STAT 24510 w/C+ or better is required; alternatively STAT 22400 w/B- or better and exposure to multivariate
calculus (MATH 16300 or MATH 16310 or MATH 19520 or MATH 20000 or MATH 20500 or MATH 20510 or MATH 20800). Graduate students in Statistics or Financial Mathematics can enroll without prerequisites. Some previous exposure to Fourier series is helpful but not required.