Final answer:
The statement is false because it mistakenly applies the probability of a confidence interval's method—which indicates a general expectation of accuracy across many intervals—to the certainty of a single confidence interval.
Step-by-step explanation:
The question posed is a statistical concept related to confidence intervals. To answer succinctly, the statement is False. There is a misunderstanding here regarding the confidence level of a confidence interval. If a confidence interval is constructed at a 90% confidence level, it means that if we were to take multiple samples and build a confidence interval from each of them, we would expect 90% of these intervals to contain the true population proportion. In the context provided, if we are talking about constructing confidence intervals for the population proportion of U.S. adults who can correctly interpret a scatterplot, and if these intervals are constructed at a 90% confidence level, then there is indeed a 90% chance that the true population proportion will be within any given interval.
However, if a single specific interval is provided, the true population proportion either is or is not within that interval — it isn't about chance for that specific interval. The idea of the confidence level applies to the method over many intervals, not the certainty of containment for a single interval. For example, comparing this with the statement that "95 percent of all confidence intervals constructed in this way contain the true value of the population mean statistics exam score", it's implied that if a 95% confidence interval is constructed for the population mean, we expect that 95 out of 100 of these intervals will contain the true mean. This is analogous to the case with the 90% confidence intervals for interpreting scatterplots.