Analysis anal·y·sis | \ ə-ˈna-lə-səs \ (noun)
a detailed examination of anything complex in order to understand its nature
Interpretation in·ter·pre·ta·tion | \ in-ˌtər-prə-ˈtā-shən, -pə- \ (noun)
a particular adaptation or version of a work, method, or style
Visualization vi·su·al·i·za·tion | \ ˌvi-zhə-wə-lə-ˈzā-shən, \ (noun)
the act or process of interpreting in visual terms or of putting into visible form*
Choices related to analytical approaches and data presentation impact the interpretation and reproducibility of an experiment. The array of options for analyzing and describing research results is broad. Knowing how to select among them without biasing the resulting output is a science in itself. Explore the topic areas listed below for more information and resources you may find relevant to your work.
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Statistics
- COS Reproducible Research and Statistics Training
- Degrees of Freedom in Planning, Running, Analyzing, and Reporting Psychological Studies: A Checklist to Avoid p-Hacking (Wicherts et al., Front Psychol. 2016)
- NIH Rigor and Reproducibility Training Module 4: Sample Size, Outliers, and Exclusion Criteria
- Statistically Speaking Ten common statistical errors from all phases of research, and their fixes (Borg DN, Lohse KR, Sainani KL. PM R. 2020)
- Statistics for Biologists
- The Extent and Consequences of P-Hacking in Science (Head et al., PLoS Biology 2015)
- Understanding Bayesian Statistics: Frequently Asked Questions and Recommended Resources
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Analysis Tools
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Validation Tools
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Pipelines
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Versioning
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Data Visualization
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Presentation of Data, Figures, Wording
- Avoiding Twisted Pixels: Ethical Guidelines for the Appropriate use and Manipulation of Scientific Digital Images (Cromey, Sci Eng Ethics 2010)
- Online Learning Tool for Research Integrity and Image Processing from ORI
- What's in a Picture? The Temptation of Image Manipulation (Rosner and Yamada, J Cell Bio. 2004)