A statistically significant result means that the evidence contradicts the null hypothesis. Statistical significance is the probability that the observed results, or more extreme ones, would occur if the null hypothesis were true.
Research Examples Rejecting Null: When a Rejected Null Indicates Statistical Significance
However, this binary label—"significant" versus "not significant"—does not measure the size or importance of the effect. The Mechanics of Rejection When a test statistic exceeds the critical value, or when the p-value drops below alpha (usually 0.
A result can be statistically significant, indicated by a rejected null hypothesis, yet be so small as to be trivial in practical application. " This does not prove that the alternative hypothesis is true, nor does it confirm the quality of the research.
Research Examples Rejecting Null and Demonstrating Statistical Significance
The strength of this evidence depends heavily on the study design, sample size, and the precision of the measurements used to gather the data. Therefore, rejecting the null hypothesis means your data produced a p-value below this cutoff, indicating that the observed effect is unlikely to be a fluke of random sampling.
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