The Crisis of Bad Data Science and What We Can Do to Avert it

  • small effect sizes,
  • large numbers of tested relationships,
  • flexibility in designs, definitions, outcomes, and analytical modes,
  • financial interests,
  • prejudices among stakeholders,
  • being a hot field,
  • solo and siloed investigators,
  • no need to pre-register tested hypotheses and ability to cherry-pick the best hypothesis after results are known,
  • no result replication,
  • no data sharing, and
  • the only statistical requirement for success being the classical 95% confidence level.



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ODSC - Open Data Science

ODSC - Open Data Science


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