Statistical power is the likelihood that a test (statistical test) will detect an effect when there is an effect there to be detected. Statistical power<span> is inversely related to </span><span>the probability of making a </span>Type II error (Type II errors<span>, or </span>false negatives, occur when you don’t see things that are there) = beta<span>. statistical power = 1 – </span>β. The critical value<span> is the </span>value corresponding to a given significance level. The statistical power<span> is </span>influenced by the choice of significance level for the test (by the critical value). Larger critical value means increased power of the test: <span> the chance of obtaining a statistically significant result is increased (reduces the risk of a </span>Type II error<span> (false negative regarding whether an effect exists) is reduced) . </span>
If a researcher establishes the critical values of a study to be more conservative, the more power the researcher has in finding significant support for a hypothesis. In the same sense, the less conservative the established critical values are, the less power a researcher has in finding significant support for a hypothesis.
The abbreviations for a tetragram, a nanosecond and a kiloliter are as follows: Tg ,ns and kl. Nanosecond is *10-9. One teragram is ten raised to the power of 9 and one kiloliter is equivalent to one thousand liters.
