Which concept is an indicator of statistical significance?

The concept of statistical significance is fundamentally linked to the p value, which is a measure used to determine the likelihood that the observed results in a study could have occurred by chance, assuming the null hypothesis is true. A low p value indicates strong evidence against the null hypothesis, suggesting that the findings are statistically significant and not likely due to random variation. Common thresholds for determining statistical significance are p values less than 0.05, 0.01, or even 0.001, depending on the field of study and the specific research question.

In contrast, while the mean value, standard deviation, and correlation coefficient are important descriptive statistics or measures of association, they do not serve as indicators of statistical significance. The mean provides a central value of a dataset, the standard deviation measures the dispersion or spread of data points, and the correlation coefficient quantifies the strength and direction of a relationship between two variables. However, none of these directly inform researchers about the probability that their results could be due to chance. Thus, the p value stands out as the key indicator of statistical significance in research analyses.