Statistical significance

Statistical significance is a statement about surprise under the null hypothesis, not about size or importance. Its biggest trap is sample size: with enough data, a difference far too small to care about still comes out significant. For example, testing $H_0: p = 0.50$ with p-hat (the sample proportion) equal to 0.51 gives $z = 0.63$ and no significance when n = 1000, but the identical 1 percentage point gap gives $z = 6.32$ when n = 100,000. Read significance next to practical significance and a confidence interval, which shows how big the effect might actually be.