1. The problem asks about the interpretation of a 99% confidence interval for a population proportion based on a sample. 2. A confidence interval is constructed from sample data to estimate a population parameter, here the population proportion $p$. 3. Important rule: The confidence level (99%) means that if we repeated the sampling many times, about 99% of those intervals would contain the true population proportion $p$. 4. The population proportion $p$ is fixed but unknown; the confidence interval varies from sample to sample. 5. The sample proportion $\hat{p}$ is a point estimate and will always lie inside the confidence interval constructed from that sample. 6. The probability statement applies to the method, not to a specific interval: we say the probability that the interval contains $p$ is 0.99 before sampling, but after the interval is computed, it either contains $p$ or not. 7. The population proportion and sample proportion are generally not equal; the sample proportion is an estimate. 8. The probability that the population proportion equals the sample proportion is not 0.99; it is a fixed value and not probabilistic. Final answer: The correct statement is "The probability that the confidence interval will include the population proportion is 0.99."