Statistics and experimental design

The objectives of the course are to introduce fundamental statistical concepts, develop data analysis and interpretation skills, and familiarize students with statistical software (R studio). It also focuses on experimental design, statistical inference, and effective data visualization. The course aims to foster critical thinking and prepares students for advanced studies in statistics or related fields.

The expected learning outcomes for the master's course in Statistical Analysis and Experimental Design include:
1. Mastery of statistical methods and techniques for data analysis in experimental research.
2. Ability to design experiments with appropriate sample sizes, controls, and randomization.
3. Proficiency in analysing and interpreting data using statistical software.
4. Understanding of the principles behind various experimental designs, including factorial, block, and repeated measures designs.
5. Knowledge of advanced regression models and multivariate analysis techniques.
6. Skills in designing and analysing experiments in real-world research contexts.
7. Development of critical thinking in interpreting results and drawing conclusions.
8. Ability to communicate statistical findings effectively in written and oral formats.