What are the consequences of using too large or too small a sample size in hypothesis testing?
- The sample size does not influence hypothesis testing
- Too large a sample size can dilute the effect size, and too small can exaggerate it
- Too large a sample size can lead to overfitting, and too small can lead to underfitting
- Too large a sample size can overstate evidence against the null hypothesis, and too small can lack the power to detect an effect
With a large sample size, small differences may become statistically significant, which can lead to overstating the evidence against the null hypothesis. In contrast, with a small sample size, we might not have enough power to detect an effect, even if one exists.
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