A 90% confidence level means that if we were to repeat the sampling process and construct confidence intervals, approximately 90% of those intervals would contain the true population parameter.
Imagine you have a bunch of identical boxes hidden around your house, and each box contains a toy. If you were to randomly select one box, there's a 90% chance that the toy inside would be within your reach.
Confidence level: The probability that the calculated confidence interval includes the true population parameter.
Significance level: The probability of rejecting the null hypothesis when it is actually true. It is often denoted as alpha (α) and represents the risk of making a Type I error.
Point estimate: An estimate of an unknown population parameter based on sample data.
A student constructs a confidence interval for the difference in proportions and finds (0.10, 0.30). What can be concluded at the 90% confidence level?
A student constructs a confidence interval for the difference in proportions and finds (0.05, 0.15). What can be concluded at the 90% confidence level?
A student constructs a confidence interval for the difference in proportions and finds (0.08, 0.18). What can be concluded at the 90% confidence level?
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