Statistics II: Experimental Design and ANOVA
• Analysis of experiments with one or more fixed and random factors, randomized block designs, crossed and nested factors.
• Multiple comparisons.
• Analysis of residuals.
• Non-parametric ANOVA, Kruskal–Wallis’ and Friedman’s tests.
• Mixed-effects models
Syllabus and other information
Syllabus
PNS0179 Statistics II: Experimental Design and ANOVA, 4.0 Credits
Subjects
Mathematical StatisticsEducation cycle
Postgraduate levelGrading scale
Language
EnglishPrior knowledge
Statistics I: Basic Statistics or equivalentObjectives
The objective of the course is to give an overview of the basic principles behind design and analysis of factorial experiments. On completion of the course, the student will be able to:
• describe basic principles in experimental design and specify analysis of variance (ANOVA) models including conditions and assumptions
• select an appropriate ANOVA model for a given experimental design
• carry out ANOVA using the statistical software R or SAS
• interpret and evaluate results correctly and draw reasonable conclusions
• clearly and concisely communicate results and conclusions
Content
The course will cover the following topics:
• Analysis of experiments with one or more fixed and random factors, randomized block designs, crossed and nested factors.
• Multiple comparisons.
• Analysis of residuals.
• Non-parametric ANOVA, Kruskal–Wallis’ and Friedman’s tests.
• Mixed-effects models
Responsible department
Department of Energy and Technology