The Model Fit Parameter Data Screen displays the Parameters, the Variance-Covariance Matrix and Summary Statistics for the selected Reliability Model fit to the Resubmission Time Series Data.  This screen is accessed by clicking the Statistics button on the Analysis Details Screen.
 

Reliability Model Parameters

The Reliability Model Parameters are coefficients that characterize a reliability model. This characterization can be seen in the mathematical expression for the Reliability Model shown on the screen.
 

Variance-Covariance Matrix
The Variance-Covariance Matrix is a tool used in fitting curves to data. The matrix shown in IntervalMAX relates to a type of fit referred to as Maximum Likelihood Estimation.

Summary Statistics
The Summary Statistics include the following:

 
Error due to Lack of Fit - standard deviation due to the Lack of Fit Sum of Squares (LSS). The LSS is the sum of the squares of the differences between the Observed Reliabilities of the Resubmission Time Series and the corresponding computed reliabilities, with the lack of fit due to inherent data scatter factored out.  The latter is referred to as the Pure Error Sum of Squares (ESS).
 
Lack of Fit Degrees of Freedom - degrees of freedom for the Lack of Fit Sum of Squares.
 

Pure Error - standard deviation due to inherent scatter in the Resubmission Time Series data.

 
F Ratio - statistic formed from the ratio of the Error due to Lack of Fit and the Pure Error.

 
Rejection Confidence - confidence for rejecting the Reliability Model shown. This confidence is computed using the F-Ratio.