The statistical method uses categories and variables which are quantifiable or can be represented by numbers, e.g., voting pattern, public expenditure, political parties, voter turnout, urbanization, population growth. It also offers unique opportunities to study the effects or relationships of a number of variables simultaneously.
It has the advantage of presenting precise data in a compact and visually effective manner, so that similarities and dissimilarities are visible through numerical representation. The fact that a number of variables can be studies together also gives the unique opportunity to look for complex explanations in terms of a relationship.
The use of the statistical method also helps explain and compare long term trends and patterns and offer predictions on future trends. A study, for example, of the relationship of age and political participation can be made through an analysis of statistical tables of voter turnout and age-categories.
Comparison of this data over long periods, or with similar data in other countries political systems, or with data showing voter turn out in terms of religious groups, social class and age can help us make complex generalizations, e.g., middle class, Hindu, male voters between the age of 25 and 30 are the most prolific voters.
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Cross national comparisons may lead to findings like, middle class women of the age group 25 to 30 are more likely to vote in western democracies than in developing countries like India. The utility of this method lies in the relative case with which it can deal with multiple variables.
It fails, however, to offer complete answers or give the complete picture. It can, be employed along with qualitative to give more comprehensive explanations or relationships and the broad categories which the statistical method uses in order to facilitate their numerical representation.