The question asks for the proportion of all possible confidence intervals that will contain the true parameter value for a 99% confidence level.

Explanation:

The confidence level directly represents the proportion of confidence intervals that will contain the true parameter value in repeated sampling. For a 99% confidence level, this proportion is 99%, or 0.99, since confidence level indicates how confident we are that the interval will include the true value.

Final Answer:

0.99

Would you like further details or explanations?

Related Questions:

1. What does a confidence interval represent in statistical terms?
2. How is a confidence level different from a probability?
3. Why is a 99% confidence level wider than a 95% confidence level?
4. How does sample size affect the width of a confidence interval?
5. What happens if the population standard deviation is unknown when calculating confidence intervals?

Tip:

Remember, increasing the confidence level (e.g., from 95% to 99%) reduces the likelihood of missing the true parameter but increases the width of the interval.