After taking this course, students can:
(Part I)
1. calculate probabilities and conditional probabilities of events, also using computer program PQRS
2. evaluate if statistical dependence holds or is violated
3. evaluate characteristics of probability density functions and apply them to different research problems
4. generate and evaluate a likelihood function for different research problems
(Part II)
5. note the difference between simulation studies, mathematical proofs, and empirical studies, and can evaluate if they can be used in particular research questions
6. identify problems that can be solved using simulation studies
7. conduct smallscale simulation studies and analyze their results using the R statistical software
8. interpret and apply dataanalysis techniques based on simulations, such as the parametric bootstrap, nonparametric bootstrap and the permutation test
(Part III)
9. apply Bayesâ€™ theorem to different research problems
10. evaluate and select appropriate prior distributions in Bayesian analysis
11. combine the prior distribution and likelihood function into the posterior distribution, using Bayesâ€™ theorem
12. test statistical hypotheses using Bayes factors using the R software
Specifics
Each module contains 4 lectures and practicals. Assignments in the practicals consist of paperandpencil and computer questions, and are graded. The grades for each module are a weighted average of the grades for these assignments. The final grade for the course is the average grade of the three module grades. The student passes the course if the average grade of the three assignments is at least 5.5, with the proviso that none of the three assignments is lower than 4.5.
If students fail for the first exam of an academic year, they can retake of one to three of the individual modules. The retake of one module comprises one allencompassing assignment. Grades of individual modules expire in the next academic year.
The grading of the course consists of two parts: the course exam (graded 110) and the SPSS practical (graded passfail). A student passes the course and receives the corresponding ects when he/she is graded a 6 or higher in the course exam and a pass in the SPSS practical. Both partial results remain valid after the academic year in which they were obtained.
Required Prerequisites
MTOB on inferential statistics, MTOCMAW on causal analysis techniques, or at least one of MTOCPSY on Experimental Research Methods and MTODPSY on Correlational Research Methods 1, or equivalent courses (subject to the decision of the programme director of MTO).
Recommended Prerequisites
