Introduction to Data-analysis [ESP03]

Detailed information about this course:

Description

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.

Please note that we are currently updating the information for 2024, therefore the course information is still subject to change.

Objectives

• 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.

Participant profile

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.

Assessment

Attendance