- CAREER COLUMN
Some data practices can lead to statistically dubious findings. Here’s how to avoid them.
By
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Benjamin Tsang
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Benjamin Tsang is a PhD candidate in the Department of Cell and Systems Biology at the University of Toronto, Canada.
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It can happen so easily. You’re excited about an experiment, so you sneak an early peek at the data to see if the P value — a measure of statistical significance — has dipped below the threshold of 0.05. Or maybe you’ve tried analysing your results in several different ways, hoping one will give you that significant finding. These temptations are common, especially in the cut-throat world of publish-or-perish academia. But giving in to them can lead to what scientists call P hacking.
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doi: https://doi.org/10.1038/d41586-025-01246-1
This is an article from the Nature Careers Community, a place for Nature readers to share their professional experiences and advice. Guest posts are encouraged.
Competing Interests
The author declares no competing interests.
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