Stat 153: Introduction to Time Series

UC Berkeley

Overview

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.

Logistics

Three hours of Lecture and Two hours of Laboratory per week for 15 weeks.

Prerequisites

134 or consent of instructor. 133 or 135 recommended.