An outlier is a data point that does not seem to fit with the others, and perhaps should be fixed or removed from the fit. A simple case is data that nicely follows a straight line, except for one point in the middle that lies far off the line. Often, this is the result of an anomaly or unexpected situation in the case that generated the data. In Adams, this might be a combination of variable values that leads to completely different model behavior, such as a part missing a stop or a linkage locking up. You can find outliers by examining
Residuals and
Cook’s Statistics for each run.
Troubleshooting: When running analytical
Design of Experiment (DOE)s, make sure that all the
Trials ran successfully. Often disk space limitations or a license server dropping off line for a few seconds can cause an entire block of runs to be missing from the results.