Erasmus Summer Programme Courses
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Introduction to Data-analysis [ESP03]
7 August 2017
11 August 2017
Monday to Friday (5 afternoons)
From 13:00 till 18:00
Prof. Adelin Albert
Erasmus MC, Rotterdam NL
An elementary knowledge in statistics acquired during a bachelor or master university degree.
- Clinical Research
- Clinical Epidemiology
Online, download instructions will be sent in August by e-mail.
A pocket calculator is required
Participants are required to bring their own laptop with the battery fully charged.
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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 will focus on modern ways to describe data such as tables, graphs, distributions and summary statistics (mean, standard deviation, median, quartiles), as required in the international scientific literature. The analysis of survival data will also be envisaged, in particular the renowned Kaplan-Meier survival curve. Finally, the association between variables will be discussed (correlation, relative risk, odds ratio and regression) as well as the agreement between observers (Cohen kappa coefficient).
The course will then turn on the relation between the population and the random sample and on how effects observed in the sample can be generalized to the total 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). 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 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 (and 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 international medical literature. The basic principles underlying non parametric tests will be outlined and the most used distribution-free tests mentioned (Spearman correlation, Wilcoxon signed rank test, Mann-Whitney U-test, Kruskal-Wallis and Friedman tests).
All topics covered in the course will be illustrated using real data from the medical and biomedical literature and applied during practical sessions.
Written exam on the Friday in the week after ESP (only for NIHES MSc students and for ‘keuzevak students’). Course materials are allowed during the examination. If other students wish to do this exam, they have to pay a fee of €75,- per exam. Credits are 1.9 ECTS when you take the exam, instead of 1.4 ECTS.
This course is equivalent to Biostatistics for Clinicians (EWP22) and Biostatistical Methods I: basic principles, part A (CC02A).
- 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.
- Students and researchers who want to have a \"rapid\" 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
Attendance, Written exam