Introduction to Data-analysis [ESP03]
Monday to Friday (5 afternoons)
Prof. Adelin Albert
Erasmus MC, Rotterdam NL
An elementary knowledge in statistics acquired during a bachelor or master university degree would be ideal but not absolutely necessary.
Detailed information about this course:
Faculty: Prof. Adelin Albert, PhD
Nobody today denies the importance of data analysis in medical practice. However, do we really understand how statistics operates and improves our scientific skills? This course is a general reminder of the basics we all should know in statistics. We review the notions of population, sample, variables and data. We show how data are summarized numerically or graphically. Based on randomness and probability, data become a powerful tool to make decisions. Emphasis will be placed on confidence intervals, hypothesis testing, and the renowned p-value. We revise the most commonly applied statistical tests including survival analysis, logistic regression and Cox models because of their wide use in the medical literature. During the course, we give a brief introduction to the "Point-and-Click" (Rcmdr) interface of the cost-free R software which is easy to use and can be of great help to the course participant.
- To refresh and reactivate your knowledge in statistics that you acquired a long time ago.
- To have a clear understanding of what statistics is all about in medicine and public health, and to be acquainted with the most commonly statistical methods used in the biomedical literature.
- To be able to assess when and how to apply these methods in real-life situations.
- To improve skills in data presentation, interpretation and communication.
- To perceive the importance of data analysis with respect to experimental planning, data collection, data reporting and data interpretation.
Students and researchers who want to have a quick refreshment of basic statistical concepts and methods; physicians and healthcare professionals who need some intelligible introduction to statistics; any person who wants a broad overview of statistical issues and methods in health sciences.
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.