Course overview
The aim of this course is to provide students with a comprehensive understanding of experimental design principles and techniques. Through theory, practical applications and use of R programming language, students will develop the skills necessary to effectively plan, conduct, and analyse experiments to enable informed decision-making across various fields, e.g., science, engineering, or business. The course builds on the foundational knowledge of probability and statistical techniques developed in earlier courses to apply these skills in the design and analysis of experiments, emphasising the importance of planning and methodological rigor in obtaining valid results.
- Foundations
- Factorial Designs
- Other Designs and Applications
Course learning outcomes
- Apply the fundamental principles of experimental design, including randomisation, replication, blocking and control to the planning and execution of experiments
- Analyse factorial experimental designs to identify patterns, resolve aliasing, and discern optimal design configurations
- Critically evaluate the design, execution, and results of experiments from own experiments or published research or industry, identifying strengths, weaknesses, and potential improvements
- Perform power calculations to determine sample size needed to identify scientifically meaningful results, using analytical or simulation-based approaches as appropriate.
- Devise a plan, simulate if needed, and analyse data from an experiment using R programming language
- Communicate experimental design and analysis of results effectively through written reports and visualisations
Degree list
The following degrees include this course