## M568 : Time Series Analysis

### Class Description

This course provides an introduction to the theory and practice of Time Series Analysis, the field of Statistics involved with the analysis of dependent data that are ordered in time. This course gives approximately equal weight to "time domain'' analysis and "frequency (spectral) domain'' analysis. It deals primarily with the usual discrete-time univariate time series, but bivariate and continuous-time processes are treated briefly.

### Class Information

**Capacity: ** Never been a problem for this course.

### Contact Information

**Instructor: **Richard Bradley - bradleyr@indiana.edu

**Other Contact(s): ** Richard Bradley - bradleyr@indiana.edu

### Other Details

**Sequence: ** No. It is a one-semester course.

**Prerequisites: ** MATH M466 or STAT S420 or consent of the instructor. The main prerequisite is a sound familiarity, at the undergraduate level, with basic real analysis, probability,and statistics, and the elementary properties of complex numbers (up to and including the form exp(it) = (cos t) + i(sin t) ).

**Algebra Required?: ** Used for notations. Used in homework.

**Calculus Required?: ** Used for concepts. Used in homework.

**Day(s) per week offered: ** Three lectures per week.

**Substantive Orientation: ** Time Series Analysis is used in numerous fields, including Economics, Engineering, Astronomy, Geology, among others

**Statistical Orientation: ** Frequentist.

**Books used: ** The main text is C. Chatfield, The Analysis of Time Series: An Introduction. Supplementary sources: G.E.P. Box and G.M. Jenkins, Time Series Analysis: Forecasting and Control; P. Bloomfield, Fourier Analysis of Time Series, An Introduction; and P.J. Brockwell and R.A. Davis, Time Series: Theory and Methods.

**Applied/Theoretical: ** Slightly more theoretical than applied.

**How the software is used: ** Data analysis

**Problem Sets: ** six written problem sets

**Data Analysis: ** Three computer assignments

**Presentations: ** None

**Exams: ** A Final Exam

**Keywords: ** The analysis of dependent data ordered in time