Title: Visualisation of a single variable
Course: UGQuants (SSPS) > Section: Data Visualisation

Visualisation of a single variable

Visual analysis of a single variable typically focuses on describing the distribution the data flow.  Three aspects of a distribution should be considered when describing the data:

The Spread | The range the data cover gives an important indication as to how dispersed data are.  This is important for placing statements about a variable in context.  From a substantive point of view, it can help describe the extent to which data vary around a typical value.
The Central Tendency or Typical Value | Visualisations provide an easy route for identifying the most common value in a distribution (the median).  This value not only provides a useful reference for discussing the values of a particular variable, but when combined with knowledge of the spread of the variable, it gives a good indication of the shape of the distribution.
The Shape | Gives an indication of how cases are spread across the distribution: are they generally gathered at one end?  Does the distribution have a single peak or more?  The identification of variables which follow the normal distribution (a single peak in the middle of the distribution, and a symmetric fall towards each end) is an important pre-requisite for many forms of statistical analysis.

Beyond describing the distribution of a given variable, certain visualisation methods (notably box-plots) can be used to identify unusual or outlying cases (those with atypical or extreme values).  Identifying such cases can help identify cases for further detailed analysis or warn about cases which might unduly influence the results of techniques such as correlation and regression.