401-3632-00L  Computational Statistics

SemesterSpring Semester 2019
LecturersM. H. Maathuis
Periodicityyearly recurring course
Language of instructionEnglish



Courses

NumberTitleHoursLecturers
401-3632-00 VComputational Statistics
On 18 April 2019 the course takes place in HG E 3.
3 hrs
Thu13:15-15:00HG F 3 »
Fri09:15-10:00HG G 3 »
18.04.13:15-15:00HG E 3 »
M. H. Maathuis
401-3632-00 UComputational Statistics
A "Präsenzstunde" directly following the exercises will be offered Friday 11-12 in HG F 3.
1 hrs
Fri10:15-11:00HG F 3 »
M. H. Maathuis

Catalogue data

AbstractWe discuss modern statistical methods for data analysis, including methods for data exploration, prediction and inference. We pay attention to algorithmic aspects, theoretical properties and practical considerations. The class is hands-on and methods are applied using the statistical programming language R.
ObjectiveThe student obtains an overview of modern statistical methods for data analysis, including their algorithmic aspects and theoretical properties. The methods are applied using the statistical programming language R.
ContentSee the class website
Prerequisites / NoticeAt least one semester of (basic) probability and statistics.

Programming experience is helpful but not required.

Performance assessment

Performance assessment information (valid until the course unit is held again)
Performance assessment as a semester course
ECTS credits8 credits
ExaminersM. H. Maathuis
Typesession examination
Language of examinationEnglish
RepetitionThe performance assessment is offered every session. Repetition possible without re-enrolling for the course unit.
Mode of examinationwritten 180 minutes
Additional information on mode of examinationThis is a computer exam. Some of the questions require the use of the statistical programming language R.
Written aidsOne sheet of paper (A4, front and back) with a machine- or handwritten summary.
Online examinationThe examination may take place on the computer.
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
CAS in Computer ScienceFocus Courses and ElectivesWInformation
Computational Biology and Bioinformatics MasterTheoryWInformation
Computational Biology and Bioinformatics MasterMethods of Computer ScienceWInformation
DAS in Data ScienceFoundations CoursesWInformation
Data Science MasterStatisticsWInformation
Computer Science MasterComputer Science Elective CoursesWInformation
Mathematics BachelorCore Courses: Applied Mathematics and Further Appl.-Oriented FieldsWInformation
Mathematics MasterCore Courses: Applied Mathematics and Further Appl.-Oriented FieldsWInformation
Micro- and Nanosystems MasterModelling and SimulationWInformation
Computational Science and Engineering MasterCore CoursesWInformation
Statistics MasterStatistical and Mathematical CoursesWInformation