Which statement correctly defines "statistical significance"?

Statistical significance is a critical concept in hypothesis testing that indicates whether the results of a study or experiment are unlikely to have occurred due to random chance given that the null hypothesis is true. This concept helps researchers determine whether the evidence against the null hypothesis is strong enough to consider it unlikely that such results could have arisen purely by chance.

When a result is deemed statistically significant, it typically means that the p-value, a measure of probability, is below a predetermined threshold (commonly 0.05). In this context, option C correctly captures that the results are unlikely to have occurred under the null hypothesis, reinforcing the notion that the observed effects or relationships in the data are likely real rather than mere flukes of randomness.

The other options do not accurately convey the essence of statistical significance; for instance, claiming that a result is due to random chance contradicts the very definition of statistical significance. Similarly, stating that results support the null hypothesis or apply only to the sample studied overlooks the broader implications of drawing inferences based on the results, which extend beyond the specific sample when statistical significance is established.