About Confidence Level and P-Value

In a Distribution Analysis, the Confidence Level and the P-Value are used to determine whether the data passes the Goodness of Fit test.

The Confidence Level indicates the percentage of uncertainty of the Goodness of Fit method. This percentage is usually determined by experience or an industry standard and limits how closely the data must fit the model in order for it to pass the Goodness of Fit test. The higher the Confidence Level, the farther apart your confidence bounds will be, and the easier it will be for your data to pass the Goodness of Fit test. The lower the Confidence Level and the closer together the bounds are, the harder it will be for your data to pass the Goodness of Fit test. If the data does pass, however, the data will be a very close fit to the model.

Note: When you enter a Confidence Level, you must specify a value that is greater than one (1) but less than one hundred (100).