With the proliferation of data mining analysis due to scanner data with tens of thousands of records,online surveys that garner thousands of respondents,and other ways to capture very large samples,there is a very real danger of finding a great deal of statistical significance that is not meaningful.

Question

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The more data that is analyzed, the greater the likelihood of finding statistically significant results, even if they are not truly meaningful or significant in terms of practical significance or impact. This phenomenon is known as the "multiple comparison problem" or "false discovery rate" and can lead to incorrect conclusions or overinflated claims. Therefore, it is important to not only look at statistical significance but also consider the context, effect size, and other relevant factors when interpreting results.

With the Proliferation of Data Mining Analysis Due to Scanner