An outlier, as the term suggests, means an observation in a sample lying outside of the "bulk" of the sample data. For example, the value "87" is an outlier in the following distribution of numbers: 2, 5, 1, 7, 11, 9, 5, 6, 87, 4, 0, 9, 7. This original meaning has been expanded to include those observations that are influential in estimation of a population quantity. Influence of an observation in estimation is intuitively understood as the degree to which the presence or absence of that observation affects the estimate in terms of the variance.
The notion of outliers is common in all statistical disciplines. However, it has a distinctive meaning in sample surveys for mainly two reasons: (1) sample surveys mostly deal with finite ...
Looks like you do not have access to this content.