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In null-hypothesis significance testing, the p-value [note 1] is the probability of obtaining test results at least as extreme as the result actually observed, under the assumption that the null hypothesis is correct. [2] [3] A very small p-value means that such an extreme observed outcome would be very unlikely under the null hypothesis.
This means that the p-value is a statement about the relation of the data to that hypothesis. [2] The 0.05 significance level is merely a convention. [3] [5] The 0.05 significance level (alpha level) is often used as the boundary between a statistically significant and a statistically non-significant p-value. However, this does not imply that ...
For the null hypothesis to be rejected, an observed result has to be statistically significant, i.e. the observed p-value is less than the pre-specified significance level . To determine whether a result is statistically significant, a researcher calculates a p -value, which is the probability of observing an effect of the same magnitude or ...
The red dashed line indicates the commonly used significance level of 0.05. If the data collection or analysis were to stop at a point where the p-value happened to fall below the significance level, a spurious statistically significant difference could be reported.
The chi-squared test indicates a statistically significant association between the level of education completed and routine check-up attendance (chi2(3) = 14.6090, p = 0.002). The proportions suggest that as the level of education increases, so does the proportion of individuals attending routine check-ups.
[3] [4] The use of a P value cut-off point of 0.05 was introduced by R.A. Fisher; this led to study results being described as either statistically significant or non-significant. [5] Although this p-value objectified research outcome, using it as a rigid cut off point can have potentially serious consequences: (i) clinically important ...
AXS-05 also met the key secondary endpoint (relapse prevention, p=0.001). Further, AXS-05 reduced the w Axsome Reveals Data From Alzheimer's Studies, Analyst Sees Hope Despite Mixed Trial Results
However, the studentized range distribution used to determine the level of significance of the differences considered in Tukey's test has vastly broader application: It is useful for researchers who have searched their collected data for remarkable differences between groups, but then cannot validly determine how significant their discovered ...