Statistical Significance the Author of Term Paper

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The relationship between the two variables, those being statistical significance and effect size is clear. A study's result may or may not be statistically significant. If it is not, then one need not really go any further. However, if it is statistical significant, the effect size should be calculated to determine whether the statistical significance is of any import. If there is statistical significance but the effect size is less than 0.1, than the statistical significance is not all that extraordinary.

This distinction is important in the studies reviewed during this course because just because one or more studies had statistical significance does nto mean that the significance is all that big a deal. The source for this report covers such an instance where a pre-test and a post-test of an examination are off by a full point (on a scale of 100) and this is deemed to be statistically significant given the size of the sample.

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However, since the difference is only one point, that difference is not nearly as significant as it may seem.

Conclusion

In the end, the existence and the relationship of statistical significance and effect size reflects a two-tiered approach that helps confirm or dismiss statistical significance based on the basic premise of whether that statistical significance is indeed significant or if it's just a trivial byproduct of the study. Using both metrics in concert is a way to reduce type I/false positive errors whereas using just statistical significance in a vacuum would lead to conclusions that are really not justified or provable based on how disparate the results really are......

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