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This course focuses on the concepts and tools behind reporting modern data analysis in a reproducible manner. Reproducible research is the idea that data analyses, and more generally scientific claims, are published with their data and software code so that others can verify the findings and build on them. The need for reproducibility is increasing dramatically as data analyzes become more complex, involving larger data sets and more sophisticated calculations. Reproducibility allows people to focus on the actual content of a data analysis, rather than superficial details reported in a written summary. In addition, reproducibility makes an analysis more useful to others because the data and code that actually performed the analysis is available.
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Associate Professor, Biostatistics
Bloomberg School of Public Health
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