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Evaluating statistical tests with enormous sample sizes

9 months ago in Impact Factor , Principal Component Analysis , Statistical Analysis By Rajiv Bhatia

Impact Factor Journals Research Paper

What factors should be considered when interpreting the results of statistical significance

In research studies with exceptionally large sample sizes, such as those analyzed using t-Student or Mann-Whitney tests, is it considered good practice to rely solely on statistical significance, and what factors should be considered when interpreting the results?

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By Roma Answered 9 months ago

While statistical tests with enormous sample sizes may yield statistically significant results, researchers should exercise caution in interpreting the practical significance and relevance of these findings. Large sample sizes can lead to statistically significant results even for trivial differences, emphasizing the importance of assessing effect sizes and practical significance alongside statistical significance. Additionally, researchers should consider the representativeness of the sample, potential sources of bias, and the context of the research question when interpreting results from statistical tests with large sample sizes. Robustness checks and sensitivity analyses can provide additional insights into the reliability and stability of the findings.

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