General description

A time series refers to a set of observations obtained at consecutive points in time. These kinds of series exist in many fields of application from economics to technology. The time dependence of the observations in most cases causes mutual dependences. The consideration of this dependence is what gives time series analysis the characteristic which separates it from other areas of statistics.

Learning outcomes

(1) The description includes both graphical and quantitative characterizations of the general features of the series.
(2) The variation of one series can be explained by the variation of some other series. Thus the same problems are touched upon that are also examined in regression analysis.
(3) We often wish to forecast future values for the series.
(4) In some applications (particularly in industry) the aim is to steer the process which produces observations in order to reach the desired goal. On the course, both simple techniques and more demanding modelling of stochastic phenomena will be discussed in order to reach the above-mentioned goals.

Contents

See objectives.

Teaching language

Finnish

Evaluation

Numeric 1-5.

Recommended year of study

2. year spring
3. year autumn
3. year spring

Study materials

1. Chatfield, C., The Analysis of Time Series: An Introduction. Chapman&Hall 1991.
2. Fuller, W. A., Introduction to Statistical Time Series. Wiley 1996.
3. Harvey, A. C., The Econometric Analysis of Time Series. Philip Allan 1990.
4. Brockwell, P. J., Davis, R. A., Introduction to Time Series and Forecasting. Springer-Verlag 1996.
5. Box, G., Jenkins, G. M., Reinsel, G., Time Series Analysis, Forecasting and Control. Holden-Day 1994.
6. Enders, W., Applied Econometric Time Series. Wiley 1995.

Belongs to following study modules