STATÂ 153 Introduction to Time Series 4 Units
Terms offered: Fall 2024, Spring 2024, Fall 2023
An introduction to time series analysis in the time domain and spectral domain. Topics will include: estimation of trends and seasonal effects, autoregressive moving average models, forecasting, indicators, harmonic analysis, spectra. This course uses either R or Python as its primary computing language, as determined by the instructor.
Introduction to Time Series: Read More [+]
Rules & Requirements
Prerequisites: 134 or consent of instructor. 133 or 135 recommended
Hours & Format
Fall and/or spring: 15 weeks - 3 hours of lecture and 2 hours of laboratory per week
Additional Details
Subject/Course Level: Statistics/Undergraduate
Grading/Final exam status: Letter grade. Final exam required.