Explain what "90\% confidence" means in a $90 \%$ confidence interval.
What does "90\% confidence" mean in a $90 \%$ confidence interval?
A. If 100 different confidence intervals are constructed, each based on a different sample of size $\mathrm{n}$ from the same population, then we expect 90 of the intervals to include the parameter and 10 to not include the parameter.

B. The confidence interval includes $90 \%$ of all possible values for the parameter.
C. The value of the parameter lies within $90 \%$ of a standard deviation of the estimate.
D. The probability that the value of the parameter lies between the lower and upper bounds of the interval is $90 \%$. The probability that it does not is $10 \%$.

Step 1 ：The question is asking for the meaning of "90% confidence" in a confidence interval. This is a concept in statistics, and it doesn't require any calculations or Python code to answer.

Step 2 ：The confidence level of a confidence interval quantifies the level of confidence that the parameter lies within the interval. In other words, a 90% confidence interval means that we would expect 90% of the confidence intervals to contain the population parameter if we drew many samples from the same population and calculated the confidence interval for each sample.

Step 3 ：So, the correct answer is option A: If 100 different confidence intervals are constructed, each based on a different sample of size n from the same population, then we expect 90 of the intervals to include the parameter and 10 to not include the parameter.

Step 4 ：Final Answer: \(\boxed{\text{A. If 100 different confidence intervals are constructed, each based on a different sample of size n from the same population, then we expect 90 of the intervals to include the parameter and 10 to not include the parameter.}}\)