Significance of Statistical Significance
Statistical significance is a critical measure in research that determines whether observed effects are likely due to treatment rather than random chance. It commonly utilizes p-values, with a threshold of less than 0.05 indicating that results are unlikely due to chance, thus suggesting true effects. This determination helps in confirming the reliability and validity of study findings, ensuring that differences observed in data are meaningful rather than attributable to random variations.
Synonyms: Statistical importance, Statistical validity, Importance, Significance
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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) The chi-square test was applied to assess differences between groups, with a P-value less than 0.05 considered to be this in the analysis.[1] (2) The likelihood that a result is not due to chance, which is determined using a P-value, to assess the reliability of the relationships found in the study.[2] (3) This is a measure used in the study to determine if the observed results are likely due to chance or if there is a real association between factors and the outcome, using a P-value.[3] (4) This is a measure of the likelihood that the observed results are due to a real effect rather than chance, and in this study, certain comparisons of characteristics and PCT levels between groups were assessed for statistical significance.[4] (5) This is the probability that a result is not due to chance, and a p-value less than 0.05 was considered statistically significant.[5]