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Irina Gaynanova | Replicability, Reproducibility, Responsibility, and Optimism for the Future of Science
Irina Gaynanova | Replicability, Reproducibility, Responsibility, and Optimism for the Future of Science
ratings:
Length:
63 minutes
Released:
Apr 27, 2021
Format:
Podcast episode
Description
Irina Gaynanova (Texas A&M) describes why she thinks that replicability is a prerequisite for reproducibility in science and how scientists can (personally) start improving the replicability of research. We also discuss how the concepts of replicability/reproducibility can differ according to the domain-specific context and the methods used.
Please forward to any students or colleagues who would find this of interest!
Please forward to any students or colleagues who would find this of interest!
Released:
Apr 27, 2021
Format:
Podcast episode
Titles in the series (88)
S00 Ep03 Pt03 with Martin Ho and Greg Maislin: The MDD Idea Exchange and Bayesian p-values: Part 3 of a three part episode with Martin Ho and Greg Maislin, talking about the ASA Section on Medical Devices and Diagnostics (MDD). This part discusses the MDD Idea Exchange and Bayesian p-values. The other two parts of this episodes cover: Part 1: ... by Data & Science with Glen Wright Colopy