The article discusses the prevalence and dangers of P hacking, a practice where researchers manipulate statistical analysis to achieve significant results. This often occurs unintentionally as researchers feel pressured to publish. Common P hacking behaviors include stopping experiments early once a significant finding is observed or reanalyzing data until a favorable P value is found. Such practices contribute to the growing reproducibility crisis in science by skewing published results that may be misleading or unfounded. Emphasizing pre-established protocols and honest analysis is crucial to mitigate these issues.
ending the experiment too early can lead to P hacking, as it risks reporting non-representative results that lack full experimental context.
one tends to focus on achieving that statistically significant finding, often sidelining the integrity of the research process in favor of immediate results.
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