1. Lesson 2

1.7. Lesson 2 Summary

Mathematics 30-3 Module 4

Module 4: Statistics

 

Lesson 2 Summary

 

This picture is of a small, yellow chick standing between three whole brown eggs with one egg on the left and two on the right.

Stockbyte/Thinkstock

 

In this lesson you investigated the following questions:

  • Why might outlying values exist in a data set, and when should they be removed?
  • How do outlying values impact the central tendency of a data set?
  • How can data that contains outlying values be interpreted?

Through Discover and Explore activities, you learned that if outliers exist in a data set, they can have a significant effect on the mean but little effect on the median and mode. If the outlying point is significantly higher than the rest of the data, then the mean is skewed upward. If the outlying point is significantly lower than the rest of the data points, then the mean is skewed downward. In either case, the outlying data can lead to misinterpretation of data.

 

Be careful when deciding to remove or trim data when calculating the mean. By removing the outliers, you are influencing the purity of the data. Trimming the data should only be done for a good reason. If you trim data, you should always be able to explain what you are doing and why it makes sense to do so.