Recommended prerequisite for participation in the module

Content, progress and pedagogy of the module

The aim of this course is to teach students how to apply statistical tools for planning, carrying out and analysing the outcomes of experiments ensuring reliable and reproducible results. the course demonstrates how to plan experiments effectively, manage qualitative and quantitative factors, and account for both controllable and uncontrollable influences. Students will develop skills in designing and analyzing factorial experiments, regression analysis, and response surface methods to optimize conditions and minimize variability.

Learning objectives

Knowledge

Students who have passed the module should be able to

• Explain the establishment of experimental design with qualitative and quantitative factors
• Account for complete, partial and confounding 2k and 3k factorial experiments
• Explain incomplete block design and splitplot designs
• Explain how to perform control experiments, including the use of central points
• Account for orthogonal experimental design
• Describe methods of optimization of the experimental factors and minimizing noise factors 
• Account for regression analysis (including step-wise regression) of the drop in data
• Explain response surface design

Skills

• Develop study plans with qualitative and quantitative factors
• Perform control experiments
• Optimize the experimental factors
• Minimize the noise factors
• Use multiple analysis of variance and regression analyzes, including the combined variance and regression analyzes
• Analyze experimental data and be able to evaluate the methods used, validity and usefulness 
• Use statistical design of experiments in practice within the domain of quality / process optimization and to process the results by statistical methods on a computer

Type of instruction

Lectures and theoretical exercises

Extent and expected workload

150 hours

Exam

Exams