<P> In statistical hypothesis testing, a result has statistical significance when it is very unlikely to have occurred given the null hypothesis . More precisely, a study's defined significance level, α, is the probability of the study rejecting the null hypothesis, given that it were true; and the p - value of a result, p, is the probability of obtaining a result at least as extreme, given that the null hypothesis were true . The result is statistically significant, by the standards of the study, when p <α . The significance level for a study is chosen before data collection, and typically set to 5% or much lower, depending on the field of study . </P> <P> In any experiment or observation that involves drawing a sample from a population, there is always the possibility that an observed effect would have occurred due to sampling error alone . But if the p - value of an observed effect is less than the significance level, an investigator may conclude that the effect reflects the characteristics of the whole population, thereby rejecting the null hypothesis . </P>

When are conclusions said to be​ statistically significant
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