What does statistical significance indicate in experimental research?

Statistical significance in experimental research indicates the likelihood that the results observed are not due to chance. When researchers report statistical significance, they are asserting that the findings are reliable and that there is a meaningful effect or difference that has been detected in the data, which suggests a genuine association rather than random variation. This can often be measured through a p-value, which helps to determine whether the observed results occur frequently due to random chance.

In conducting experiments, researchers establish a threshold for statistical significance, typically at a p-value of 0.05 or lower, which indicates that there is only a 5% or smaller probability that the results occurred due to random chance. Thus, the correct interpretation of statistical significance is rooted in this idea of ruling out chance as a plausible explanation for the findings.

Regarding the other options, they do not accurately convey the essence of statistical significance. The first option incorrectly implies a newsworthy outcome is only considered significant if it is positive, which misrepresents the concept. The second option states that the likelihood of results being due to chance is what statistical significance measures, which actually describes a complementary aspect to significance rather than its definition itself. The last option confuses statistical significance with the strength of the relationship, which involves correlation or