How to Avoid P Hacking

P-hacking is significant for all researchers because the statistical results can only be interpreted at face value, when every choice in data analysis was performed exactly as planned and documented as part of the experimental design.

Join Jim Colton, M.S., Lead Statistician at GraphPad, as he uncovers the truth behind this controversial practice and explores its implications on data integrity and research credibility analysis in this video.

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