Chapter 10

In This Chapter

Learning how to identify outliers with formal statistical procedures

Seeing how outliers affect statistical tests

Finding out how to avoid the problems associated with outliers

An *outlier* is a member of a dataset that’s significantly larger or smaller than the other values in the dataset. Outliers can appear in all walks of life. For example, the following would be considered outliers:

- A man who is seven feet tall
- A woman who is 100 years old
- A household that has an annual income of $100 million per year
- A baseball player who hits .400 during an entire season

In statistical analysis, an outlier refers to a value that is substantially different from the other values within a sample or a population. For example, suppose you take a sample of housing prices in a small town, with the following results (in hundreds of thousands of dollars):

240, 270, 290, 305, 332, 348, 371, 404, 2,250

In this case, you would consider the home that’s worth $2.25 million to be an outlier because it’s so much more expensive than the other homes in that town. In fact, it’s more than five times as costly as the next most expensive ...

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