Final answer:
We can never have a 100 percent confidence interval due to variability and uncertainty in data, the fluctuation of population parameters, and limitations in statistical calculations.
Step-by-step explanation:
The reason we can never have a 100 percent confidence interval is due to variability and uncertainty in data. When constructing a confidence interval, we are trying to estimate a population parameter based on a sample. However, there will always be some degree of uncertainty and variability in the data, which prevents us from having a 100 percent confidence in our interval.
For example, even if we take repeated samples and calculate confidence intervals from those samples, only a certain percentage of those intervals will actually contain the true value of the population parameter. This is due to the fluctuation of population parameters and the limitations in statistical calculations.
In addition, accuracy limitations in sampling techniques and limitations in statistical calculations can also contribute to the inability to have a 100 percent confidence interval.