Course overview
This course aims to equip students with essential statistical methods and analytical tools vital for human factors research. The focus is on developing robust understanding and skills in executing various statistical tests, from foundational concepts to advanced analysis techniques. By learning topics such as descriptive statistics, null hypothesis significance testing, programming with statistics software packages, data visualization, parametric and non-parametric methods, and advanced topics like regression, latent variable analysis, and General Linear Model, students will be prepared to conduct rigorous and meaningful research in human factors, ensuring they can effectively analyse data, and interpret results within real-world applications.
- Fundamentals of Statistics for Human Factors
- Hypothesis Testing and Inferential Statistics
- Advanced Statistical Methods
Course learning outcomes
- Describe fundamental statistical principles for human factor research.
- Analyse the results from practical statistical tests commonly used in human factor research.
- Apply statistical computing software to perform data manipulation, execute various statistical tests, and create impactful visualisations.
- Examine research designs and data quality, using statistical techniques and measures to ensure research standards.