Understanding Outliers and Measures of Center

The video tutorial from Mumu Math explains the concept of outliers and their impact on measures of center, specifically the median and mean. It demonstrates how to identify an outlier in a data set and calculates the changes in median and mean when the outlier is removed. The tutorial concludes with a rule of thumb: use the median when an outlier is present and the mean when there is no outlier.

What is an outlier in a data set?

• A value that is the average of all others

• A value that is repeated multiple times

• A value that is much higher or lower than the others

• A value that is exactly in the middle

Which score is identified as the outlier in the given data set?

• 94

• 55

• 90

• 88

How much did the median change when the outlier was removed?

• 0.5

• 3.0

• 1.5

• 2.0

What is the effect of removing the outlier on the mean?

• The mean increases by 1.5

• The mean remains the same

• The mean decreases by 7.25

• The mean increases by 7.25

Which measure of center is more affected by the outlier?

• Range

• Mean

• Mode

• Median

When is it best to use the median as a measure of center?

• When there are no outliers

• When the data set is small

• When there is an outlier

• When the data set is large

What should you use when there is no outlier in the data set?

• Range

• Mode

• Mean

• Median