401-6624-11L  Applied Time Series

SemesterSpring Semester 2020
LecturersM. Dettling
Periodicityyearly recurring course
Language of instructionEnglish



Courses

NumberTitleHoursLecturers
401-6624-11 VApplied Time Series2 hrs
Mon10:00-12:00ER SA TZ »
10:15-12:00HG E 1.1 »
M. Dettling
401-6624-11 UApplied Time Series1 hrs
Mon/2w08:00-10:00ER SA TZ »
08:15-10:00HG D 1.1 »
M. Dettling

Catalogue data

AbstractThe course starts with an introduction to time series analysis (examples, goal, mathematical notation). In the following, descriptive techniques, modeling and prediction as well as advanced topics will be covered.
ObjectiveGetting to know the mathematical properties of time series, as well as the requirements, descriptive techniques, models, advanced methods and software that are necessary such that the student can independently run an applied time series analysis.
ContentThe course starts with an introduction to time series analysis that comprises of examples and goals. We continue with notation and descriptive analysis of time series. A major part of the course will be dedicated to modeling and forecasting of time series using the flexible class of ARMA models. More advanced topics that will be covered in the following are time series regression, state space models and spectral analysis.
Lecture notesA script will be available.
Prerequisites / NoticeThe course starts with an introduction to time series analysis that comprises of examples and goals. We continue with notation and descriptive analysis of time series. A major part of the course will be dedicated to modeling and forecasting of time series using the flexible class of ARMA models. More advanced topics that will be covered in the following are time series regression, state space models and spectral analysis.

Performance assessment

Performance assessment information (valid until the course unit is held again)
Performance assessment as a semester course
ECTS credits5 credits
ExaminersM. Dettling
Typesession examination
Language of examinationEnglish
RepetitionThe performance assessment is offered every session. Repetition possible without re-enrolling for the course unit.
Mode of examinationwritten 120 minutes
Written aidsarbitrary written aids, pocket calculator
This information can be updated until the beginning of the semester; information on the examination timetable is binding.

Learning materials

No public learning materials available.
Only public learning materials are listed.

Groups

No information on groups available.

Restrictions

There are no additional restrictions for the registration.

Offered in

ProgrammeSectionType
DAS in Data ScienceStatisticsWInformation
MAS in Sustainable Water ResourcesElective CoursesWInformation
Statistics MasterTime Series and Stochastic ProcessesWInformation
Environmental Sciences BachelorMethodes of Statistical Data AnalysisWInformation
Environmental Sciences BachelorMethodes of Statistical Data AnalysisWInformation