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6 Simple Rules to Ensure Efficiency and Data Integrity
In 2016, a major survey found that over 70% of life science researchers were unable to reproduce findings of other scientists and approximately 60% of researchers could not reproduce their own results (Baker 2016). Lack of reproducibility in research is a growing problem that threatens data integrity and the credibility of the scientific community in general. In the lab, it results in lower scientific output, reduced efficiency, and wasted time and resources.
Access tips for improving reproducibility in lab results from this infographic which lists six rules to follow for improving lab performance and scientific quality.
These steps include:
- Minimizing uncertainty
- Eliminating bias
- Practicing documentation
- Standardizing traceability
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