2.2.2 - Outliers

Some observations within a set of data may fall outside the general scope of the other observations. Such observations are called outliers. Outliers can be identified by looking at a dotplot or histogram. In Lesson 3 you'll learn about boxplots which can also be used to identify outliers. When constructing a boxplot, Minitab identifies outliers using mathematical methods that you will see next week. This week we will identify outliers by making a relatively subjective judgement from a given a list of data points, a dotplot, or a histogram.

Example: Dotplot of Hours Watching TV Section

A sample of STAT 200 students was surveyed and asked how many hours per week they watch television. A dotplot was constructed using these data.

Dotplot of Hours Per Week Watching TV Hours Per Week Watching TV Each symbol represents up to 3 observations 0 12 24 36 48 60 72


The right-most dot is definitely an outlier because it is much higher than any other points. The other higher points, around 55, 50, and 46, may be outliers. Next week we will learn about some mathematical methods for identifying outliers that can help us make decisions in cases like this where it is not obvious which values are outliers. 

Example: Histogram of Best Marriage Age Section

This sample of students was also asked what they believed was the best age to get married. A histogram was constructed using these data.

30 0 50 100 150 200 250 45 60 75 90 Histogram of Best Marriage Age Best Marriage Age Frequency


There appear to be three outliers in this sample, all on the higher end.