What does 'statistical significance' indicate?

Statistical significance indicates that the results of a study are unlikely to have occurred by chance. This concept is crucial in research as it helps determine whether the observed effects in the data reflect true underlying patterns rather than random fluctuations. Researchers typically set a threshold (often a p-value of less than 0.05) to signify that the likelihood of the results being due to chance is sufficiently low, thus favoring the conclusion that there is a meaningful effect or relationship present.

This understanding is essential in various research fields, as it provides a basis for making informed decisions and drawing conclusions from the data collected. Achieving statistical significance raises confidence in the findings and supports further exploration and application of the results.

While the other options touch on important aspects of research, they do not accurately capture the essence of what statistical significance is specifically indicating. For instance, the idea of results being purely experimental or replicable across studies relates to the design and reliability of research but does not define statistical significance. Similarly, real-world applications might be impacted by statistically significant results, but they are not inherent to the definition of statistical significance itself.