Page 38 - Quantitative Data Analysis

Quantitative Data Analysis
Simply Explained Using SPSS

Outliers

An outlier is an “extreme” value that does not fit in normal range of
values. Outlier is an influential data point that can dramatically
change the mean value.

1. Lower bound for an outlier:

1. A value in the data falling below the lower bound is
considered an outlier.

2. Upper bound for an outlier:

3. A value in the data falling above the upper bound is
considered an outlier.

If a data set has one or more outliers, the marker of the maximum
(or minimum) on the box-and-whisker plot is replaced by the (or
) and a dot is placed at the outliers.

With reference to the data set in last example,
;

IQR:

Thus any value in the data set below 16.5 or above 30.50 will be
considered as an outlier. Because no values are below 16.50 or
above 30.50, this dataset has no outliers.

The Theory and Applications of Statistical Inferences 22