The best way to avoid p-hacking is to use preregistration. P-hacking is inevitable, but there can be safeguards in play that can help in reducing instances of data dredging and help avoid the trap. However, it can have severe implications such as an increase in the number of false positives leading to the study’s retraction, misleading other operations, increased bias, and a gross waste of resources. P-hacking is unintentional cherry-picking of promising note-worthy data that can lead to an excess of significant and desirable results. Data dredging or p-hacking is one of the most common ways in which data analysis is misused to find patterns that appear statistically significant but are not.ĭata dredging is very difficult to spot and mainly affects the study in negative ways. The results in data science too are also highly dependent on the data analysis process. We all know that the product is as good as the processing technique. Practices of data collection and analysis in industry and academics may not be outright fraud, but one cannot completely deny the existence of malpractices.
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