How do you interpret a 95% confidence interval in hypothesis testing?
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A 95% confidence interval in hypothesis testing means that if we were to repeat the sampling process many times, approximately 95% of the calculated confidence intervals would contain the true population parameter.
If a 95% confidence interval does not contain the value under H₀, the null hypothesis is rejected at α = 0.05.