What is a confidence interval?
A range of values so defined that there is a specified probability that the value of a parameter lies within it.
The purpose of taking a random sample from population and computing a statistic, such as the mean, is to approximate the mean of the population. How well the sample statistic estimates the underlying population value is always an issue. A confidence interval addresses this issue because it provides a range of values which is likely to contain the population parameter of interest.
Confidence intervals are constructed at a confidence level, such as 95 %, selected by the user. What does this mean? It means that if the same population is sampled on numerous occasions and interval estimates are made on each occasion, the resulting intervals would bracket the true population parameter in approximately 95% of the cases.
Why have confidence interval?
Confidence intervals are one way to represent how “good” an estimate is; the larger a 95% confidence interval for a particular estimate, the more caution is required when using the estimate.
Confidence Intervals in ProcessModel
To obtain confidence interval data, multiple replications must be run. To setup a model for multiple replications go to the Simulation/Options menu and set the number of replications. Set the number of replications and uncheck the animate checkbox.