Inhalt

### [ 445IWMEASIK23 ] KV Applied Statistics for Engineers

Versionsauswahl
Workload Education level Study areas Responsible person Hours per week Coordinating university
3 ECTS M1 - Master's programme 1. year Statistics Markus Hainy 2 hpw Johannes Kepler University Linz
Detailed information
Original study plan Master's programme Mechanical Engineering 2023W
Objectives The students can correctly understand and interpret statistical information. Given some data, they are able to select the appropriate graphical and tabular displays as well as statistical indicators to adequately describe the (joint) distribution of the data. The students understand the principle of statistical hypothesis tests and can apply this principle, among other things, to testing the differences in proportions and mean values of samples from two different populations. Furthermore, the students can apply the method of linear regression to estimate linear causal relationships and are able to assess the quality of the linear fit. The students are aware of the importance of carefully planned experiments, especially in technical applications. They are familiar with some of the major types of experimental designs, such as factorial and fractional factorial designs, and understand their fields of application, advantages, and limitations.
Subject
• Collecting and presenting data (tables, graphics)
• Measures of location, dispersion, and association/correlation
• Probability distributions (especially normal and survival distributions)
• Confidence intervals and hypothesis tests for proportions and mean values (one-sample and two-sample tests), chi-squared test for association
• Linear regression: modeling, fit and interpretation, checking the model assumptions
• Design of experiments: factorial, fractional factorial, and central composite designs
Criteria for evaluation Written exam, number of submitted homework examples
Methods Lecture (using slides and the blackboard), discussion of homework examples
Language German
Study material
• Schiefer, H. & Schiefer, F. (2018): Statistik für Ingenieure. Eine Einführung mit Beispielen aus der Praxis. Springer Vieweg, Wiesbaden
• Ryan, T. P. (2007): Modern Engineering Statistics. Wiley, Hoboken
• Kleppmann, W. (2020): Versuchsplanung. Produkte und Prozesse optimieren. 10. Auflage. Carl Hanser Verlag, München
Changing subject? No
Further information The solution of the examples is regularly illustrated by employing Minitab so that students get used to utilizing statistical software for solving common statistical problems.
On-site course
Maximum number of participants -
Assignment procedure Assignment according to priority