Type II error

Definition: A false negative result occurs when the alternative hypothesis is true in the population but the null hypothesis is accepted as part of the analysis (Hartgerink et al., 2017). That is, finding a non-significant statistical result when the effect is true (For example, a judge passing an innocent verdict on a guilty person). False negatives are less likely to be the subject of replications than positive results (Fiedler et al., 2012), and remain an unresolved issue in scientific research (Hartgerink et al., 2017).

Related terms: Effect size, Null Hypothesis Significance Testing (NHST), Questionable Research Practices or Questionable Reporting Practices (QRPs), Reproducibility crisis (aka Replicability or replication crisis), Scientific integrity, <a href='/glossary/statistical-power/'>Statistical power</a>, True positive result, <a href='/glossary/type-i-error/'>Type I error</a>

References: Fiedler et al. (2012), & Hartgerink et al. (2017)

Drafted and Reviewed by: Olly Robertson, Mahmoud Elsherif, Charlotte R. Pennington

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