TILS619 Time Series Analysis (2–5 cr)

Study level:
Advanced studies
Grading scale:
0-5
Language:
Finnish
Responsible organisation:
Department of Mathematics and Statistics
Curriculum periods:
2024-2025, 2025-2026, 2026-2027, 2027-2028

Description

Time-series is a dataset consisting of observations recorded at consecutive time instants. Time-series typically have serial correlation.

We discuss in the course, for instance, the following topics:

  • graphical exploration of time-series (for instance using autocorrelation and partial autocorrelation)
  • stationarity,
  • linear time-series models (ARIMA), choosing a model, estimation of its parameters, and prediction using the model.

The main emphasis of the course is on ARIMA-models, but different instances of the course have varying additional content, such as:

  • frequency domain methods (such as periodogram),
  • multivariate time-series, and/or
  • state-space models

Learning outcomes

Student who completes the course successfully:

  • can draw and interpret the sample autocorrelation of a time-series,
  • recognises time-series, which can be considered stationary,
  • can choose a suitable ARIMA-model for a time-series, 
  • can investigate the fit of the model
  • can use the model for prediction, including a confidence interval.
In addition, students who complete the 5 credit version of the course understand theory behind the methods.

Additional information

Degree students in statistics and data science take the 5 credit course. Degree students from other fields can take either 2 credit or 5 credit course.

The course will be lectured (at least) every 1.5 years.

Description of prerequisites

,5 credits: Statistical inference 1 and 2; Further probability.

2 credits: Data visualization and analysis and From data to model or equivalent background; familiarity with basic usage of R.

Completion methods

Method 1

Evaluation criteria:
Arviointiin vaikuttavat menestys kurssikokeessa ja mahdollisesti aktiivisuus harjoitustehtävien tms. tekemisessä sekä harjoitustyöstä suoriutuminen.
Select all marked parts

Method 2

Evaluation criteria:
Kurssin loppukokeessa hyväksyttyyn suoritukseen vaaditaan yleensä vähintään puolet tentin maksimipisteistä.
Select all marked parts
Parts of the completion methods
x

Teaching (2–5 cr)

Type:
Participation in teaching
Grading scale:
0-5
Language:
Finnish

Teaching

x

Exam (2–5 cr)

Type:
Exam
Grading scale:
0-5
Language:
Finnish
No published teaching