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What does a confidence level of 95% indicate?

There is a 5% chance that the result is incorrect.

A confidence level of 95% indicates that if you were to conduct the same study repeatedly and build a confidence interval from each sample, approximately 95% of those intervals would capture the true population parameter, such as the mean. Therefore, there is a 5% chance that a given confidence interval does not include the true population mean, which aligns directly with the interpretation of a 95% confidence level. This concept reflects the reliability of the estimate and represents the level of uncertainty regarding the results derived from the sample data.

The other options do not convey the meaning of a confidence level: a specific sample size isn't required to achieve a 95% confidence level; the population mean cannot be known definitively just from a sample; and results from a sample are not universally applicable unless further conditions are met.

The sample size must be at least 100.

The population mean is definitively known.

The results are universally applicable.

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