# Statistical significance

In statistical hypothesis testing,[1][2] a result has statistical significance when a result at least as "extreme" would be very infrequent if the null hypothesis were true.[3] More precisely, a study's defined significance level, denoted by ${\displaystyle \alpha }$, is the probability of the study rejecting the null hypothesis, given that the null hypothesis is true;[4] and the p-value of a result, ${\displaystyle p}$, is the probability of obtaining a result at least as extreme, given that the null hypothesis is true.[5] The result is statistically significant, by the standards of the study, when ${\displaystyle p\leq \alpha }$.[6][7][8][9][10][11][12] The significance level for a study is chosen before data collection, and is typically set to 5%[13] or much lower—depending on the field of study.[14]