Guide to Essential BioStatistics III: Type I and Type II errors

In this third article in the LabCoat Guide to BioStatistics series, intended as a basic refresher for scientists and technicians, we learn about Type I and Type II errors. A Type-I error would lead us to reject the Null hypothesis, claiming that there IS a difference between treatments (false positive) when there is none. A Type-II error would lead us to not reject the Null hypothesis, erroneously concluding that there is NOT a difference in phytotoxicity between the treatments. #statistics #biostatistics #experimentalresearch #cropprotection #bioscience #GuideToEssentialBiostatistics #Experimentaldesign
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