MTTTS18 Time Series Analysis 1 5 ECTS
Organised by
Degree Programme in Mathematics and Statistics
Corresponding course units in the curriculum
School of Information Sciences
Curricula 2015 – 2017
MTTTS18 Time Series Analysis 1 5 ECTS

Learning outcomes

After the course, the student will be able to characterize the basic properties of a time series and decompose it into a trend, seasonal component and noise. He will also be able to identify and diagnose linear time series models, estimate their parameters and use them in forecasting. Further, he will be able to use the periodogram to detect possible periodic components in the series.

Contents

Simple time series models, stationary time series models (ARMA), nonstationary and seasonal time series models (SARIMA), time series regression, periodogram.

Modes of study

Option 1
Available for:
  • Degree Programme Students
  • Other Students
  • Open University Students
  • Doctoral Students
  • Exchange Students
Participation in course work 
In English
Option 2
Available for:
  • Degree Programme Students
  • Other Students
  • Open University Students
  • Doctoral Students
  • Exchange Students
Written exam 
In English

Evaluation

Numeric 1-5.

Study materials

Brockwell, Davis: Introduction to Time Series and Forecasting, Springer, 2nd ed,  2010

Belongs to following study modules

Faculty of Natural Sciences
2017–2018
Teaching
Archived Teaching Schedule. Please refer to current Teaching Shedule.
Faculty of Natural Sciences