732A34 Time Series Analysis
Time series analysis is the field of statistics where we study data that in one or the other way may change with time. Striking examples are different kind of economic and business data (sales and income figures, consumer price indices, interest rates, unemployment figures, stock market indices etc.) Most of the data collected at supplies departments at different companies are time series data. The application is however not limited to this sector. A lot of temporal data are collected in the production lines within industries, where the time scales can be of completely different orders (milliseconds instead of months). Another very important field is natural science and in particular environmental information. Weather data of different kinds are nowadays of partcular interest with respect to ongoing debates about the climate.
Time Series Analysis, 6 credits is a profile course within the Master's program in Statistics and Data Mining.
The aim, contents and teaching of the course can be read in the syllabus (under the link to the left).
The organisation of the course during the study year 2013/2014 is in the form of one or two weekly meetings. These meetings will be a mixture of lectures and exercises. You should benefit on bringing a laptop to the meetings, but it is by all means possible to share a laptop with someone else during the sessions. Many exercises are of that kind that a computer must be used. In the course we will use R as software (partly because the course book is focused on R) but you are of course free to use other software (e.g. SAS) if you wish.
A number of exercises will be given as assignments to be individually carried out. That part is not supposed to take place at the weekly meetings, but outside the schedule. There will not be any supervision for these assignments since they are part of the examination, but they can be carried out in the computer rooms or at home. No other statistical software than R will be needed. The solutions to the assignments should be submitted in forms of written reports. The core text of these reports may contain graphs and tables, but the latter should be constructed from scratch (i.e. no copying and pasting from R or other software). Besides such components the text should be completely your own and easy to read. Direct outputs from the software (except graphs) can only be included in form of attachments. In the marking of these reports, emphasis will be put on the English language. It will not be sufficient to simply give short answers to the detalied questions of the exercises.
Cryer J.D., Chan K-S. (2008) Time Series Analysis - With Applications in R 2nd ed. Springer. (ISBN 978-0-387-75958-6)
Course tutor and examiner
Ann-Charlotte Hallberg, e-mail: Ann-Charlotte.Hallberg@liu.se
Office: Building B, Entrance 27, upstairs, corridor E
Tutor works only part-time at the department and the easiest way to get in contact is at the weekly meetings and by e-mail.
Page responsible: Anders Nordgaard
Last updated: 2013-07-25