The statistical significance of data is communicated through something called a p-value, which is the probability of obtaining our results in a universe where our null hypothesis is true. P-hacking can lead to academic papers headlined with false positives, such as tobacco smoking improving health or vaccinations damaging the human body. ![]() If a researcher runs ninety-nine statistically insignificant experiments before obtaining a statistically significant one, and they only report the significant one in a scientific paper, that individual is guilty of p-hacking. Thus, in our Coca-Cola experiment, our null hypothesis would be the claim that everyday consumption of Coca-Cola has no significant positive correlation with fitness.ĭata dredging, also called p-value hacking, stems from reporting cherry-picked statistically significant results from a set of tests while intentionally leaving out the necessary context of the majority statistically insignificant ones. In other words, a null hypothesis is a statement researchers build just to hopefully knock down. In hypothesis testing, researchers formulate a null hypothesis - which is the idea that the variables we are testing do not affect the results.
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