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[Q] How is There Any Truth In Hypothesis Testing If Any Confidence Level Can Be Chosen?
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NFeruch is a queer person
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I'm learning about hypothesis testing for data science, and am concerned about the credibility of hypothesis testing in the real world. In the example that I was working through (actual problem not important), the t-statistic given was less than our threshold of alpha=0.025 for a left-tailed test (forgive me if this is not the correct way to put it) and therefore we failed to reject the null hypothesis. But then I realized, what if I had just chosen a confidence level of say, 95%, rather than our 97.5%. When choosing the former over the latter, the value was greater than our threshold, and the null was rejected.
In the real world, what stops me from choosing a different confidence level that fits my narrative, even if it's biased?
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