Answer:
d. 0.05.
Explanation:
If an interval estimate is said to be constructed at the 90% confidence level, the significance level would be d. 0.05.
Confidence level and significance level are two different concepts in statistics. The confidence level refers to the probability that the interval estimate contains the true population parameter. In this case, a 90% confidence level means that if we were to construct multiple interval estimates using the same method, we would expect about 90% of them to contain the true parameter.
On the other hand, the significance level, also known as the alpha level, is the threshold at which we determine whether to reject or fail to reject the null hypothesis in a hypothesis test. The significance level is typically set before conducting the test and represents the maximum acceptable probability of making a Type I error, which is rejecting the null hypothesis when it is actually true.
In the given question, the interval estimate is constructed at the 90% confidence level. Since the confidence level is 90%, it means that there is a 10% chance that the true population parameter falls outside the interval estimate. This corresponds to a significance level of 0.10 or 10%.
Therefore, the correct answer is d. 0.05.