An important practice is to check the validity of any data set that you analyze. One goal is to detect typos in the data, and another would be to detect faulty measurements. Recall that outliers are observations with values outside the "normal" range of values of the rest of the observations.

• Specify a large population that you might want to study and describe the type of numeric measurement that you will collect (examples: a count of things, the height of people, a score on a survey, the weight of something) for your study.
• What is the best course of action statistically if you found few outliers in a sample of size 100?

To answer the above questions:

• Outline the method (s) you will use if two values twice as big as the next highest value were identified in the sample.
• You may use examples from your area of interest, such as monthly sales levels of a product, file transfer times to different computer on a network, characteristics of people (height, time to run the 100-meter dash, statistics grades, etc.), trading volume on a stock exchange, or other such things.