Assessing Product Reliability
8.2.3. How can you test reliability model assumptions?
|A visual test of a model is a simple plot that tells us at a glance whether the model is consistent with the data||
We have already seen many examples of visual tests of models. These were: Probability Plots, Cum hazard Plots, Duane Plots and Trend Plots. In all but the Trend Plots, the model was "tested" by how well the data points followed a straight line. In the case of the Trend Plots, we looked for curvature away from a straight line (cum repair plots) or increasing or decreasing size trends (inter arrival times and reciprocal inter-arrival times).
These simple plots are a powerful diagnostic tool since the human eye can often detect patterns or anomalies in the data by studying graphs. That kind of invaluable information would be lost if the analyst only used quantitative statistical tests to check model fit. Every analysis should include as many visual tests as are applicable.
Advantages of Visual Tests
|Combine visual tests with formal quantitative tests for the "best of both worlds" approach||Disadvantages of Visual Tests