eventFundamentals of Statistics with Introduction to Kalman Filters for Technical, Economical and Biological Systems [Fundamentals of Statistics with Introduction to Kalman Filters for Technical, Economical and Biological Systems ] (V)
person Paolo Mercorelli

Next appointment: 12. October at 18:15
This course belongs to the Wintersemester 2026/2027!

Dates

weekly | Monday | 18:15 - 19:45 | 12.10.2026 - 29.01.2027 | C 40.106 Konrad-Zuse-Raum

Curriculum context

Combined academic performance
presentation during seminar (25%)
report on seminar project (software) (75%)
Date of assessment: Wednesday, 31.03.2027
Resit date: No resit date will be offered to this assessment, because it is didactically inseparably connected with one of the associated courses. A resit will only be possible, if the module is available again.
Anzeige von Anmeldebeginn und -ende systembedingt. Selbständige Anmeldung nur zum Prüfungstermin und nicht zum Wiederholungstermin möglich.

Organizational information

Lecture
Vollständig Präsenz
2
centralized multi stage lottery procedure with cluster (with participant limit)
15

Registration

centralized multi stage lottery procedure with cluster (with participant limit)

Registration does not begin until 02.10.2026 at 08:00. It ends on 12.10.2026 at 23:59.

This course belongs to the cluster "Komplementärstudium".

In this cluster, you have one choice during the lottery phases.
And in the decision phase 3 choices.

Persons

Content

Englisch
Fundamentals of Statistics with Introduction to Kalman Filters for Technical, Economical and Biological Systems
Methodenorientiert - naturwissenschaftlich
Nachhaltigkeitsorientiert

This course is designed to provide a foundational understanding of statistics with a particular focus on applying statistical concepts to the Kalman filter, which is widely used in fields like signal processing, control systems, and machine learning. The course will cover essential statistical methods and their applications, culminating in the introduction of the Kalman filter and its mathematical framework.Applications for technical, economical and biological systems.

By the end of this course, students will:
1. Understand fundamental concepts in statistics, including probability, distributions, hypothesis testing, and regression.
2. Learn key statistical techniques such as estimation, maximum likelihood, and least squares fitting.
3. Gain an understanding of the Kalman filter, its mathematical foundation, and its application to time-series data.
4. Develop the skills to implement the Kalman filter in practical applications.


Prüfungsinformationen zum Komplementärstudium finden Sie unter: http://www.leuphana.de/college/studium/ks.html

Evaluation

This course has not been registered for teaching evaluation yet.

Further information on teaching evaluation: https://www.leuphana.de/en/teaching/quality-management/evaluation/course-evaluation.html

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