Fundamentals Statistical Tools
An easy and applied introduction to key statistical concepts. Learn about data visualisation & outlier detection. Demystify statistical significance testing – p-values, significance, power, confidence, etc. An excellent introductory module and a solid basis for all other courses.
Biostats in the Medical Literature
Learn key biostatistical concepts to review & interpret findings published in the medical literature. Selected scientific publications are reviewed, discussed and criticised in terms of bias, uncertainty & scope.
Introduction to the Design of Experiments ‘DOE’
Variation is present in every experiment. Learn about DoE techniques to control variation, and to maximise data quality. Commonly used experimental designs are discussed as well as corresponding statistical data analysis tools.
Advanced Experimental Designs
Learn about advanced experimental designs to account for constraints: time, resources, material heterogeneity, randomisation restrictions as well as repeated measures. The construction of advanced designs and their analysis is covered.
Screening Techniques in DOE
In preliminary research phases, the number of potentially influential factors to investigate is usually large. Screening designs are essential to identify the most influential factors with a reasonable number of runs in preliminary research phases.
Optimisation Designs
Once influential factors are identified, the next goal consists of optimising their settings. This module covers the construction of experimental designs for optimisation. Data modelling is carried out with response surface methodology.
Statistical Analysis of Metagenomic Data
Metagenomic data possess specific features that call for adapted statistical methods. Learn about the most commonly used statistical tools in this field.
Statistical Methods for Reliability Studies
In industrial applications, reliability is crucial and testing is expensive. Collected data must be exploited in the best way possible. Reliability data possess specific features that call for dedicated statistical methods. Learn about statistical tools for reliability analysis.