Lecture Professor Heinz Pitsch

Thursday, 12:30 - 14:00, H09 (CARL) (12.10.2023 - 01.02.2024)

Exercise Christian Schwenzer

Thursday, 14:30 - 15:15, H09 (CARL) (12.10.2023 - 01.02.2024)

Exam

Friday, 09.02.2024, 08:30 - 10:00, H02 (CARL)

LV-Registration: RWTHonline

For Lecture and Exercise, a joint moodle page (VO) is used.

Lecture and Exercise material: RWTHmoodle

Introduction to the meaning of measurement data, measurement uncertainty and data analysis.

• Acquisition, presentation and management of measurement data
• Challenges in the acquisition of measurement data based on examples
• Introduction of statistical parameters
• Data management and data life cycle
• Measurement uncertainties
• Introduction of different measurement uncertainties
• Determination of measurement uncertainties and error propagation (Part 1)
• Determination of measurement uncertainties and error propagation (part 2)
• Calibration and verification of the measurement technique
• Data analysis
• Filtering of data and data visualization
• Hypothesis testing and functional relationships by means of regression
• Data analysis with machine learning methods (introduction)
• Data analysis with machine learning methods (examples)
• Application of the learned methods in MATLAB

Accompanying the lecture, exercises are offered in which the students apply the acquired
methods and concepts using real data sets.

Notice:

The lecture "Measurement Techniques and Data Analysis" has a scope of 3 ECTS.