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Fundamentals of Statistics and Data Science
In this course, the basic principles of statistical inference are presented, with an emphasis on likelihood methods. Methods are illustrated by the classical linear model.
Generalized Linear Models
The course will expand the linear model to include link functions such as the logit with binomial and the log with Poisson error distributions.
Prognosis Research (online)
In this course, principles and methods of non-experimental prognosis research will be discussed.
Systematic Reviews in Intervention Research
We will discuss the strengths and limitations of meta-analysis, and provide step-by-step guidance on how to perform a meta-analysis based on examples.
Presenting Your Research Confidently
You will learn how to improve preparation and presentation skills. You will discover how to design visuals, structure your presentation, get and keep the audience’s attention, make good use of your voice and body language, handle audience’s questions
Survival Analysis (online)
Survival data, or time-to-event data (the “event” can be death, disease or another outcome), is frequently encountered in epidemiologic studies. Censoring is a problem characteristic of most survival data and requires special data analytic techniques
Public Health Epidemiology (online)
Public health epidemiology involves describing and interpreting geographical and temporal patterns, identifying prevention strategies, estimating and evaluating the impact of risk factors and preventive measures on population health.
Advanced Diagnostic Research
Diagnostic research in the past focused particularly on estimating the sensitivity and specificity of individual diagnostic tests. This course will demonstrate that this so called ‘test research’ is not necessarily the same as diagnostic research.
Classical Methods in Data Analysis (f2f)
Topics are: types of data, location and variability measures, samples and populations, distributions, confidence intervals, hypothesis testing, comparing two or more means or proportions, and relationships between two variables.
Mixed Models
Starting with analysis of summary statistics on each individual's observations, this course will lead you to more advanced methods for analyzing multilevel and longitudinal data.
