Product Development Issues
When analyzing data, you will sometimes find one value that is far from the others. Such a value is called an outlier. When you encounter an outlier, you may be tempted to delete it from the analysis. Assuming that the data point is not attributable to obvious experimental mistakes, do you keep it or delete it?