# data[].attributes.body
it changes because there is a range of numbers in that area, and it changes from a number much farther from the cluster than the rest of the numbers, for example, here is a data set 12,15,13,25,1. there are two outliers in this data set. they are out of the range of the cluster of numbers.

# data[].attributes.body
it depends where the outlier is on the data

# data[].attributes.body
it really only is the outlier because it is the range and it changes it

# data[].attributes.body
it changes because your adding a whole new number to the data set

# data[].attributes.body
Roman the mean will change because it will count as a number in the data set and u will have to add it

# data[].attributes.body
The mean can change the answer because it can make the answer bigger or smaller.

# data[].attributes.body
The outlier can change an average dramatically. If a data set is 34 37 35 and 71 then the outlier (71) would change the mean completely

# data[].attributes.body
It pushes it up or down adds or subtracts the mean

# data[].attributes.body
The mean changes when there is an outlier because because the mean is the average and the average will change because one number is either way bigger or way smaller then the rest which is an outlier.

# data[].attributes.body
The mean either gets up or goes down because you are adding new numbers to the data set

# data[].attributes.body
It changes because the outlier counts as another number added to the data set

# data[].attributes.body
the mean becomes higher or lower with the outlier depending were it is in the data set

# data[].attributes.body
The mean changes because you are adding another number on to the end or the begining  so the data set changes, changing the mean.

# data[].attributes.body
The mean changes because the outlier pushes the mean up or down depending on if the outlier is bigger or smaller than the rest of the data set