Reproducible Science

In times of "Faked News" and "Alternative Facts" especially the reproducibility of scientific results is targeted in this learning resource.

Introduction
Reproducibility is the ability to get
 * (Result) the same research results or inferences,
 * (Data)
 * based on the same raw data or
 * with data collected with the same or very similar sampling and research procedures (replicability)
 * and finally

A related concept to reproducibility is replicability, meaning the ability to independently achieve non identical conclusions that are at least similar, when differences in sampling, research procedures and data analysis methods may exist. Reproducibility and replicability together are among the main beliefs of ‘the scientific method’ - with the concrete expressions of the ideal/idea of such a method varying considerably across research disciplines and fields of study.
 * (Algorithms)the same computer programs (e.g. Open Source R or KnitR) provided by researchers.
 * (Capacity Building) optional access to capacity building material allows other scientist re-use the provide approach for their experimental design (see Open Educational Resources)

Learning Tasks

 * Explore the KnitR concept of integration of content, data and algorithms for data processing.
 * Compare the following two different scenarios:
 * A researcher collects data and applies a several methodologies of data analysis (statistical and/or numerical approaches) to the data until a significat publishable result was found.
 * A researcher has to publish a KnitR document (R-Markdown) prior to sampling the data. After sampling is finished the data was processed with the KnitR document and results will be published as significant or not significant.
 * Analyse the WHO Document about clinical trial . Explain, why is it important to publish negative results (e.g. statistical bias)! Why does the publication of negative results contribute to concept Reproducibility?

External References

 * Foundation for Open Access Statistics (FOAS) - Statistical Perspective on Reproducible Science,