Introduction to Data-analysis [ESP03]
Monday to Friday (5 afternoons)
Prof. Adelin Albert
An elementary knowledge in statistics acquired during a bachelor or master university degree.
Detailed information about this course:
Faculty: Prof. Adelin Albert, PhD
This course is a general introduction to the basics of statistics used in biomedical and public health applications. We start with a general definition of statistics and give some examples. We then review the notions of population, sample, variables (qualitative and quantitative) and data (missing, outlying, and censored). Next, the course focusses on ways to describe data such as tables, graphs, distributions and summary statistics (mean, standard deviation, median, quartiles) as reported in medical journals. Lifetime data will be visualized graphically by the celebrated Kaplan-Meier survival curve. Association measures between variables (correlation, regression, relative risk, odds ratio and hazard ratio) as well as agreement measures between observers (Cohen kappa coefficient) will be discussed.
The course will then turn on the relation between the population and the random sample and on how characteristics observed in the sample can be generalized to the population. Some elementary probability elements will be needed here. This will lead to the important concepts of standard error and confidence intervals (for means, proportions, odds ratios, hazard ratios). The general theory of hypothesis testing will be briefly outlined from an intuitive perspective and the fundamental concepts of statistical significance, power calculation and p-value will be introduced. Then, we shall review some of the most frequently used testing procedures: correlation test, unpaired and paired t-tests for comparing two means values, analysis of variance for comparing several means (with multiple tests correction), chi-squared test (Fisher exact test) for comparing two proportions and more generally for contingency tables, McNemar test for paired proportions, and two-way analysis of variance for repeated data. The logistic model and Cox model will be briefly alluded to because of their importance in the medical literature. Finally, the basic principles underlying non parametric tests will be outlined and some of the most used distribution-free tests presented (Spearman correlation, Wilcoxon signed rank test, Mann-Whitney U-test, Kruskal-Wallis and Friedman tests).
During the course, a brief introduction to the R statistical software will be given to participants. R is free of charge, increasingly used worldwide, but not easy to learn for the layman due to its tedious programming language. There is however a 'Point-and-Click' interface for R called the 'R Commander' or simply 'Rcmdr' which is really easy to learn and use. Thus, students will acquire some familiarity with the R Commander, do basic statistical calculations and draw nice graphs even on large datasets.
Topics covered in the course will be illustrated using real data from the medical literature. Participants will also use Rcmdr during the course.
This course is equivalent to Biostatistics for Clin
//Pleasenote that the course information is subject to change and will be updated fromtime to time. We will do our utmost best to ensure the accuracy and reliability of the information on this website.//
- 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 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.
- To perform basic statistical analyses and graphs using the statistical "Point-and-Click" software Rcmdr even if familiar with well-known statistical packages as SAS, SPSS or Stata.
- 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 RESEARCH MASTERS (120 EC points)
50% reduction on our fees for participating institutes of NIHES
This 50% reduction is offered to participants formally appointed at the departments or sections participating in NIHES.
University Medical Center Rotterdam/Erasmus University Rotterdam:
- Department of Epidemiology
- Department of Public Health
- Department of Psychiatry, Section of Medical Psychology and Psychotherapy
- Department of Child and Adolescent Psychiatry/Psychology
- Department of Medical Informatics
- Department of General Practice
- Erasmus School of Health Policy & Management
- Generation R
50% reduction on our fees for NIHES affiliated partners
This 50% reduction is offered to participants formally appointed at the following NIHES affiliated partners:
University Medical Center Rotterdam/Erasmus University Rotterdam, departments of:
- General Paediatrics
- Plastic and Reconstructive Surgery
- Rehabilitation Medicine
UMIT, Department of Public Health, Health Services Research and Health Technology Assessment.
25% reduction on our fees for Erasmus MC employees
For participants formally appointed at all departments of Erasmus MC (except the departments mentioned above).
25% reduction for all (international) PhD students
Please upload proof of enrollment as a PhD student in the application form and state the name of your tutor on the application form (remarks field).
25% reduction on our course fees (maximum 3 EC points per academic year) for all NIHES alumni
Please state that you are a NIHES alumnus/alumna and the academic year you graduated (remarks field). Please note that the reduction on fees for alumni does not apply to the Erasmus Summer Programme.