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If the confidence level is not provided in the question, it is typically assumed to be 0.95 or 95%. This is a common default confidence level used in many statistical analyses and hypothesis testing unless stated otherwise.

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Final answer:

A confidence interval is a range of values that estimates the true value of a population parameter with a specified level of confidence. It does not necessarily contain a certain percentage of the data. In this study, a 90% confidence interval was constructed to estimate the true population parameter.

Step-by-step explanation:

A confidence interval is a range of values that estimates the true value of a population parameter with a specified level of confidence. In statistics, a 90% confidence interval means that if we were to repeat the experiment many times and construct 90% confidence intervals using the same method, about 90% of these intervals would capture the true population parameter. So, a 90% confidence interval does not necessarily contain 90% of the data, but rather expresses our level of confidence in estimating the true population parameter.

In this particular study, a 90% confidence interval was constructed using a set of data. The resulting interval provides a range of values within which we can be 90% confident that the true population parameter lies. This interval does not guarantee that 90% of the data falls within it, but instead reflects our level of confidence in estimating the true population parameter.

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