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732G06 Time Series Analysis

Course information


LINKÖPINGS UNIVERSITET                                732G06 TIME SERIES ANALYSIS

Institutionen för datavetenskap                                           Fall semester 2008

Statistik/And                                                              COURSE INFORMATION.

 

 

                     

                     

Welcome to the course in Time Series Analysis

Formal information about course contents can be read in the course curriculum. We will just briefly present some of the contents further below.

 

About 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 such as sales figures, income figures and unemployment figures. Most of the data collected at supplies departments at different companies are time series data. The application is however not limited to this sector. E.g. another very important field is natural science and in particular environmental information. At the division of Statistics at Linköping University an environmental statistics research group is established, where a lot of the research deals with times series data.

 

We will in this course get familiar with different basic methods of time series analysis. The focus will mainly be on learning how to apply the methods and interpret the results that come out of them. More theoretical aspects of time series analysis are given in the course Time Series Analysis, advanced course.

Organisation of the course

The course will be organised briefly as follows:

Each week we will have a meeting (a mix of lecture, tutorial and discussion seminar) in which we will present and discuss the core of that week’s stuff and the learning from previous weeks.. You should prepare this meeting by reading the corresponding parts in the textbook. The rest of the week you mostly work on your own with exercises that most often must be done on a computer. Solutions to some of the exercises should be submitted successively and they are part of the examination in the course (see further below). You are encouraged to co-operate with each other doing exercises, but each one of you must submit his (or her) own solution to every exercise. During the last weeks of the course you will be given a larger exercise (project work) that should be done in smaller groups (2 or 3 persons).

A brief working plan can be found as a link on the course web page. There is also a link “Updated information” where you successively may find useful information (changes in schedule etc.) or linked documents to be used. Check this link now and then during the course.

 

Schedule

The course starts on Wednesday 27 of August at 13.15 in room John von Neumann located in building B, entrance 27, 2nd floor, corridor D (uppstairs from Cafe Java). The rest of the course will be scheduled in co-operation with you as it is difficult to overview the schedules of all the other courses you will attain. As far as possible we will try to have the weekly meetings on Thursdays and Fridays. You will have access to the computer rooms PC1-PC5 (located in building E, entrance floor), but there are other courses scheduled there and I will provide you with information about available time-points.

 

Examination

 

The course will be examined by solutions of the given exercises and by a final oral exam with questions around the different parts. The grades in the course are Failed, Passed and Passed with Distinction translated to ECTS-grades for exchange students. To receive the degree Pass you must do all the given exercises and the project work and give acceptable solutions and answers to the questions. To receive the degree Pass with Distinction the requirements on the solutions and the answers are higher.

 

Course contents

 

Classical descriptive time series analysis with methods for decomposition. Forecasting with exponential smoothing and Box--Jenkins ARIMA--models. Practical examples from mainly economics and business administration. Use of standard statistical computer packages for time series analysis.

 

Literature

 

Bowerman, B.L, O'Connell, R.T. and Koehler, A.B.: Forecasting and times series-an applied approach. 4rd ed.  Thomson Brooks/Cole, 2005. (ISBN 0-534-40977-6)

Complementary handouts

 

Teachers

 

Course leader and tutor:

Anders Nordgaard, tel. 013-281974, e-mail: annor@ida.liu.se

You will meet me in my office (Building B, Entrance 27, uppstairs, corridor E, Thursday-Friday)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 


Page responsible: Anders Nordgaard
Last updated: 2008-06-27