The amount of evidence required to accept that an event is unlikely to have arisen by chance is known as the significance level or critical p-value: in traditional Fisherian statistical hypothesis testing, the p-value is the probability of observing data at least as extreme as that observed, given that the null hypothesis is true. Many researchers urge that tests of significance should always be accompanied by effect-size statistics, which approximate the size and thus the practical importance of the difference. Research analysts who focus solely on significant results may miss important response patterns which individually may fall under the threshold set for tests of significance. As used in statistics, significant does not mean important or meaningful, as it does in everyday speech. The phrase test of significance was coined by Ronald Fisher. Statistical Significance - From Wikipedia In statistics, a result is called "statistically significant" if it is unlikely to have occurred by chance. Probability - Probability Error Less Than.
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