The results are called statistical significance when a difference in treatment is decided to be due to more than random chance.
In order for a result to be considered statistically significant, an analyst must conclude that it cannot be solely attributed to chance. The analyst reaches this conclusion via statistical hypothesis testing.
With the assumption that the findings are actually the product of pure chance, this test yields a p-value, which is the likelihood of seeing outcomes as severe as those in the data. It is often accepted that a p-value of 5% or less indicates statistical significance.
Statistical significance is frequently used in pathology research, vaccination testing, and pharmaceutical medication trials to determine the efficacy of new medicines and to update investors on the company's progress.
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