A confidence level of \( 95 \% \) means: \( 95 \% \) of the time, sample percentages will fall above the mean. \( 95 \% \) of the time, population data will fall between 149.61 and 150.39 . the mean of \( 95 \% \) of the adults in the sample was 150 . OONE:

To clarify the concept of a confidence level of \( 95\% \), let's break down the statements provided: 1. **\( 95\% \) of the time, sample percentages will fall above the mean.** - This statement is incorrect. A \( 95\% \) confidence level means that if we were to take many samples and calculate the confidence interval for each sample, \( 95\% \) of those intervals would contain the true population parameter (mean). It does not imply that \( 95\% \) of sample percentages will fall above the mean. 2. **\( 95\% \) of the time, population data will fall between 149.61 and 150.39.** - This statement is misleading. A \( 95\% \) confidence interval means that we are \( 95\% \) confident that the true population mean falls within the interval (in this case, between 149.61 and 150.39). It does not mean that \( 95\% \) of the individual data points in the population will fall within this range. 3. **The mean of \( 95\% \) of the adults in the sample was 150.** - This statement is somewhat vague. It suggests that the sample mean is \( 150 \), but it does not directly relate to the concept of a \( 95\% \) confidence level. The sample mean is used to estimate the population mean, and the confidence interval is constructed around this sample mean. ### Conclusion: The most accurate interpretation of a \( 95\% \) confidence level is that if we were to take many samples and construct confidence intervals from those samples, \( 95\% \) of those intervals would contain the true population mean. If you have a specific question or need further clarification on any of these points, please let me know!