Time series analysis and forecasting

4 days
In English on request

During this course you will learn and practice modern approaches to time series analysis, modeling and forecasting.

Modern methods for time series analysis, modelling and forecasting

In analyzing time series one searches for structures and patterns to describe and explain the underlying process. But also for ways to use adequate models fitted to predict future values or to study the effects of alternative scenarios.

Time series occur in a wide range of disciplines, from business, economic and social sciences to biomedical and engineering contexts. This course treats actual methods for time series analysis, modelling and forecasting.

Apart from the traditional methods for trend and seasonal decomposition of time series, more advanced statistical techniques, both in the time-domain and in the frequency domain are discussed and underlying principles are explained.

Insight in and practice with time series

During this course you will learn, in a hands-on manner:

  • You gain insight in current approaches for time series analysis, modelling and forecasting, specifically:
    • Exponential Smoothing models (Simple, Holt, Holt-Winter)
    • Box-Jenkins models (ARMA, ARIMA, SARIMA)
    • Multivariate time series modesl for correlated series (dynamic regression and VARMA models)
  • You learn to analyze, to model and to validate time series data using relevant statistical software such as R, Minitab or JMP
  • You learn to use the models obtained for time series analysis forecasting and scenario analysis

Intended for

Academics and professionals who have to analyze and predict time series data in their work. The course is also suited for lecturers at universities or colleges of higher education who want to be informed on actual methods for time series analysis.

Kennis van statistische basistechnieken zoals toetsen, schatten en regressiemodellering wordt bekend verondersteld. Praktische voorbeelden zijn in R.

In English on request

Do you want to follow the course in English? Please mention this in the remarks field when you register.

Course leader

Data analysis and programming

dr. Koo Rijpkema

Eindhoven University of Technology (TU/e)

“For me, teaching means sharing knowledge and passion, inspiring and fascinating people through the application of statistics.”

This course is rated with an average of


Program manager


  • The latest post-academic knowledge and skills
  • Focused on questions that arise in a technical environment
  • Interactive and directly applicable in practice
  • Top teachers from science, research and business

Frequently asked questions

  • "Goed uitgelegd, en vaak verwijzing naar eerder uitgelegde onderdelen. Ook oefenen met de stof was aanwezig."
    Marc de Wolf
    ASML Netherlands BV
  • "De cursus was een zeer nuttige inleiding tot tijdsreeksanalyse en bevat veel aanknopingspunten voor verdere studie."
    Centraal Planbureau
  • "Leuke introductie met een goed overzicht van de basisblokken in de tijdreeksanalyse."
    Jan Willem Goemans
    Provincie Noord-Holland
  • "Mooie combinatie van grondslagen en praktische vaardigheden."
    Ministerie van Justitie en Veiligheid
  • "Diepgaand, goed theoretisch onderbouwd, met voldoende praktijkelementen."
    Martijn van Eeten
    IHC Holland BV
  • "De cursus is in veel opzichten leerzaam. Theoretische deel was inspannend en intensief."
    Achmea Expertise
  • "Leerzame cursus, ik wil hier veel mee doen in mijn dagelijks werk."
    NV Nederlandse Gasunie
  • "De cursusstof is inhoudelijk helder gepresenteerd en er is orde aangebracht in de vele methodes."
    Participant working at Belastingdienst Utrecht
  • "Intensieve cursus, met praktisch inzicht in de theorie van tijdsreeksen."
    Coöperatie VGZ
  • "Deep dive in toegepaste statistiek op tijdreeksvoorspelling."
    Stefan Manders
    ING Bank

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