Biostatistics I [CK020]
Monday-Friday, the course covers a fulltime workload.
Prof. Dimitris Rizopoulos, PhD, Eleni Rosalina Andrinopoulou, PhD, Nicole Erler, PhD, Joost van Rosmalen, PhD
Participants are expected to have a basic knowledge of standard mathematical concepts to the level of the CK001 course (formerly BST01). NIHES programme students should have completed CK001.
Detailed information about this course:
This course is offered in a hybrid setting, which means students can join the live lecture in class and online simultaneously.
This course provides an introduction to the basic concepts and techniques of statistical data analysis. The course starts with a presentation of fundamental notions of statistics and statistical inference under uncertainty. The course then continues with an in-depth presentation of classical regression models, namely, linear regression for continuous data, logistic regression for dichotomous data. Classical statistical parameter and non-parametric statistical tests are linked to these models. For each modeling framework, a detailed discussion is given on how to build the model to answer the scientific questions of interest, estimate the model’s parameters, assess its assumptions, and finally, interpret the results of the analysis.
The course will be explanatory rather than mathematically rigorous, emphasizing application such that participants will obtain a clear view of the different modeling approaches and how they should be used in practice. To this end, the course includes several computer sessions, during which participants will learn to work with the R statistical language and implement the methods discussed in the theory sessions.
For students in our master programmes, the core concepts presented in this course will be assessed in the core competences exam that bundles the fall semester courses. This is in addition to the assessment during the course in the form of assignment(s). The core competences exam is only mandatory for students starting their programme in August 2021 or later, while the assignments during the course are mandatory for all participating students.
At the end of the course, participants will have learned:
- The basic concepts of statistical inference
- When and how to use standard statistical tests
- When and how to use statistical regression models
- How to assess the assumptions behind the chosen statistical analysis technique
- How to correctly interpret the results of the analysis
- How to implement all the above in the R statistical software
Clinical researchers, clinical epidemiologists, decision scientists, public health researchers, those in health technology assessment or value-based healthcare.
Reduction on fees
PLEASE NOTE: This does not apply to the fee of the research master programmes (120 EC points)
No fees are charged for Erasmus MC PhD candidates, provided they have an account in Hora Finita, the Erasmus University PhD registration system. When submitting the application, you can state that someone else pays your tuition fee.
In case of cancellation or no show, the cancellation policy applies based on the full course fee.
25% reduction for all (international) PhD candidates without formal appointment at Erasmus MC
Upon receipt of your application you will receive a request to upload proof of enrollment as a PhD candidate.