The Effect of Outliers on Mean & Median

Knowledge Builder:
What is an Outlier? An outlier is a piece of data that is numerically different from the others, in which case is placed outside the representation of the cumulative data.

What is Mean? Well you could basically think of mean as being another way of saying the average. Mean is taking the sum of all values in a set of data and dividing it by the total number of values.

What is Median? Median can be explained in a variety of ways: The numerical value separating the upper and lower half of a sample, in an even number of observations the median is determined by finding the mean of the two middle values. But we are gonna keep it simple and define median as the middle value in a set of values arranged in numerical order.

Lesson:
So now that we have some background knowledge on mean, median, and outliers we can move on to the bigger question. How do outliers affect the mean and median? As explained in the knowledge builder outliers are basically values that do not belong in a set of data for numerical reasons. They kind of screw with the way the data is represented.
Here is an example of an outlier in a box and whisker plot:
Mean:21
Median:25
UQ:33

LQ:23                                                                                      The outlier in this data would be 49 and is clearly marked with an astrick. 

                                                                         

= Outlier 49