Before deciding whether or not to omit outlying values from a given data set, first, obviously, we must identify the data set's potential outliers. Generally speaking, outliers are data points that differ greatly from the trend expressed by the other values in the data set - in other words, they lie outside the other values. It's usually easy to detect this on data tables or (especially) on graphs. If the data set is expressed visually on the graph, outlying points will be "far away" from the other values