Final answer:
A confidence interval indicates with a certain level of confidence whether the true population parameter lies within a specified range calculated from the sample data. It consists of a point estimate plus or minus a margin of error and is used to infer about the population from a sample.
Step-by-step explanation:
A confidence interval (CI) is an interval estimate used to quantify the uncertainty associated with a sample statistic. It provides a range of values that, with a certain level of confidence, is believed to contain the true population parameter.
The correct statement about confidence intervals is that it indicates whether the parameters are different from zero. The interval consists of a point estimate, which is typically the mean of the sample data, plus or minus a margin of error. The margin of error accounts for the desired confidence level and the variability of the sample (often represented by the standard error).
Confidence intervals do not measure the degree of association between cost and activity output, determine activities for a process, nor provide a guarantee that the actual cost will always coincide with the predicted cost.
The process of constructing a CI typically involves finding the point estimate, deciding on the confidence level (e.g., 95% or 99%), and calculating the margin of error using a critical value (such as a Z-score or t-score) and the standard error of the mean.
Interpretation of a confidence interval must be done in context; it does not provide absolute certainty but rather indicates a range where the true parameter is likely to be found, given the chosen confidence level.
Therefore, the correct option is d. it indicates whether the parameters are different from zero.