English
Advanced studies
Degree Programme in Mathematics and Statistics
Faculty of Natural Sciences
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.
Enrolment for University Studies
Enrolment time has expired
Teachers
Hyon-Jung Kim-Ollila, Teacher responsible
hyon-jung.kim[ät]tuni.fi
Teaching
25-Oct-2017
–
13-Dec-2017
Lectures
Wed 25-Oct-2017 - 6-Dec-2017 weekly at 12-14, Pinni A2088
Exceptions:
15-Nov-2017
, ML B1084, exercises
6-Dec-2017
, Independence Day, no lecture (scheduled later).
Mon 30-Oct-2017 - 11-Dec-2017 weekly at 12-14, Main Building A2a
Fri 1-Dec-2017 at 12-14, B0016
Exercises
Wed 25-Oct-2017 - 6-Dec-2017 weekly at 14-16, Pinni A2088
Exceptions:
15-Nov-2017
, lecture
6-Dec-2017
, Independence Day, no teaching (scheduled later).
Fri 1-Dec-2017 at 14-16, Pinni B ML40 (B0040)