An outlier has a greater effect on the mean. This is because the mean is a balan

Question

An outlier has a greater effect on the mean. This is because the mean is a balancing point (average) while the median is simply the center number. Example: Consider the data set 50, 50, 50, 50, 50. Clearly this has a mean of 50 and a median of 50. Now let’s add an outlier. Consider 50, 50, 50, 50, 50, 200. The median is still 50 but the mean is now 75. The outlier clearly had a bigger effect on the mean.

Question 1: Explain whether an outlier has a greater effect on the mean or median. Given an example to illustrate this. Write your answer in a Word document.

Explanation / Answer

Outliers affect mean the most. This is because mean is calculated by adding the values in the data set. Whereas median is the middle most value in the data.

Consider the following data

0.15

0.11

0.06

0.06

0.12

-0.56

In the above data -0.56 I an outlier. When we caclualte mean including this value, it is -0.01. When we calculate mean without including -0.56, we get 0.1

When we calculate median using -0.56, we get 0.085, without -0.56, mrdian is 0.11.

From the calculations we understand that mean is affected more than median by outiers.

0.15

0.11

0.06

0.06

0.12

-0.56

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