Note that, when calculating outliers, the median is usually assigned the variable Q2 - this is because it lies between Q1 and Q3, the lower and upper quartiles, which we will define later. However, if there are an even number of points, then, since there is no single middle point, the 2 middle points should be averaged to find the median. X Research source If the data set contains an odd number of points, this is easy to find - the median is the point which has the same number of points above as below it. The median of a data set is the data point above which half of the data sits and below which half of the data sits - essentially, it's the "middle" point in a data set. If 11 of the objects have temperatures within a few degrees of 70 degrees Fahrenheit (21 degrees Celsius), but the twelfth object, an oven, has a temperature of 300 degrees Fahrenheit (150 degrees Celsius), a cursory examination can tell you that the oven is a likely outlier.Ĭalculate the median of the data set. Let's consider a data set that represents the temperatures of 12 different objects in a room.If, for instance, the majority of the points in a data set form a straight line, outlying values will not be able to be reasonably construed to conform to the line. X Research source If the data set is expressed visually on the graph, outlying points will be "far away" from the other values. It's usually easy to detect this on data tables or (especially) on graphs. 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. 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. Learn how to recognize potential outliers.
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