# Statistical significance

## Concept in inferential statistics / From Wikipedia, the free encyclopedia

#### Dear Wikiwand AI, let's keep it short by simply answering these key questions:

Can you list the top facts and stats about Statistical significance?

Summarize this article for a 10 year old

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 $\alpha$, 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, *$p$*, 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 $p\leq \alpha$.^{[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]}

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.^{[15]}^{[16]} But if the *p*-value of an observed effect is less than (or equal to) the significance level, an investigator may conclude that the effect reflects the characteristics of the whole population,^{[1]} thereby rejecting the null hypothesis.^{[17]}

This technique for testing the statistical significance of results was developed in the early 20th century. The term *significance* does not imply importance here, and the term *statistical significance* is not the same as research significance, theoretical significance, or practical significance.^{[1]}^{[2]}^{[18]}^{[19]} For example, the term clinical significance refers to the practical importance of a treatment effect.^{[20]}