Measures of Center with Outliers

The video tutorial explains the three measures of center: mean, median, and mode. It highlights that mode is not a reliable measure of center as it can be skewed by data extremes. The mean is suitable when there are no outliers, as outliers can significantly affect the average. The median is preferred when outliers are present, as it accurately represents the center without being influenced by them. The tutorial concludes with an example data set containing an outlier, demonstrating why the median is the best choice for summarizing the data.

Which measure of center is not reliable when it can be at the high or low end of a data set?

• Median

• Mean

• Range

• Mode

When is it appropriate to use the mean as a measure of center?

• When the data set is small

• When there are outliers

• When the data set is large

• When there are no outliers

Why should the mean be avoided if there are outliers in the data set?

• It is the same as the mode

• It is difficult to calculate

• It can be greatly affected by outliers

• It is not a measure of center

Which measure of center is best used when outliers are present?

• Mode

• Mean

• Standard Deviation

• Median

How does the median help in representing the center of a data set with outliers?

• It averages all values

• It ignores the outliers

• It calculates the most frequent value

• It shows the center without being affected by outliers

In the given data set, why is the median chosen over the mean?

• The data set has no mode

• The data set is too large

• The data set has an outlier

• The data set is too small