Significance of Statistical Significance
Statistical significance is a critical concept in research, indicating that the results of a study are unlikely to have occurred by chance, often assessed using a p-value threshold of less than 0.05. This measure determines whether observed effects represent true differences rather than random variability. By evaluating the likelihood that findings, such as treatment outcomes or differences between groups, are due to chance, statistical significance helps validate the real-world implications of research findings and ensures reliable conclusions.
Synonyms: Statistical importance, Statistical validity, Importance, Significance
The below excerpts are indicatory and do represent direct quotations or translations. It is your responsibility to fact check each reference.
The concept of Statistical Significance in scientific sources
Statistical Significance indicates whether study results are likely due to chance or represent a real effect, assessed through p-values, and is essential for validating improvements observed post-treatment through statistical analysis.
From: The Malaysian Journal of Medical Sciences
(1) This refers to the likelihood that the results of a study are due to a real effect rather than chance, as described in the text.[1] (2) The level at which the results of a study are considered unlikely to have occurred by chance, defined at the 5% level in the analysis.[2] (3) This is a threshold (P < 0.05) used in statistical analysis to determine if the observed results are likely due to a real effect rather than chance.[3] (4) Statistical significance is determined using statistical tests to identify if observed differences between experimental groups are unlikely due to random chance, P < 0.05.[4] (5) This refers to the likelihood that the results of a study are not due to chance, and in the study, the difference in mean rank scores between males and females was statistically significant.[5]