Before employing inferential statistics, Alberto selects the probability level required for statistical significance. this level is referred to as the alpha level of the test.
The significance level also called alpha or α, is a measure of the strength of evidence that must be present in the sample before the null hypothesis can be rejected and an effect can be concluded to be statistically significant. The researcher determines the significance level before conducting the experiment.
For statistical tests, statistical significance is determined by specifying the alpha level, or the probability of rejecting the null hypothesis given that it is true.
The significance level, also called alpha or α, is the probability of rejecting the null hypothesis if it is true. For example, a significance level of 0.05 indicates a 5% risk of concluding that there is a difference when there really isn't.
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