A 95% confidence interval is a statistical range, derived from sample data, that is expected to contain the true population parameter with a probability of 95%. This means that if we were to take many samples and build a confidence interval from each one, approximately 95% of those intervals would capture the true value of the parameter being estimated. This concept is essential in making inferences about populations based on sample statistics, particularly in the context of odds ratios and confidence intervals.
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