Making Research Reproducible
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Format: In-person or online
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Duration: Full-Day Workshop
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Includes: Comprehensive workshop notes and reference materials, access to statistical package and certification of completion
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In-House Resource:
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Overview
This workshop aims to equip researchers, students, and professionals with the necessary skills to ensure their research is reproducible. Reproducibility is a cornerstone of scientific integrity, enhancing the credibility and utility of research findings. The course covers methodologies, tools, and best practices for planning, conducting, and documenting research in a manner that allows others to replicate the results.
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Key Topics
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Fundamentals of Research Reproducibility
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Designing Reproducible Studies and Experiments
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Statistical Methods for Reproducibility
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Tools and Technologies to Facilitate Reproducible Research (e.g., R, Python, Git, Docker)
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Documentation and Open Science Practices
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Case Studies and Examples of Reproducible Research
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Learning Outcomes
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Understand the importance of reproducibility in research.
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Learn techniques to design studies that are inherently more reproducible.
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Gain knowledge of statistical methods that enhance reproducibility.
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Familiarise with tools and software that aid in replicable research practices.
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Implement effective documentation and data sharing practices.
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Analyse and learn from real-world examples of reproducible research.
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Who Should Attend?
Researchers, academics, postgraduate students, and any professionals engaged in empirical research. Prior experience with basic research methodology is beneficial but not required.
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Why Attend?
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Improve the reliability and credibility of your research.
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Contribute to the advancement of open and transparent scientific practices.
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Enhance your research skills in line with current best practices.
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Facilitate collaboration and sharing within the research community.
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Stay abreast of the latest tools and techniques in reproducible research.
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Format
An interactive mix of lectures, practical exercises, group discussions, and case study analyses. The workshop will focus on applying principles of reproducibility in various research scenarios.
