Bivariate analysis is concerned with the relationships
between pairs of variables (X, Y) in a data set. Bivariate
analysis, explores the concept of association between two variables. Bivariate analysis is
based on how two variables simultaneously change together, that is, the notion of
Using bivariate analysis we test hypotheses of
"association" and causality. Association refers to the extent to which it
becomes easier to know/predict a value for the Dependent variable if we know a case's
value on the independent variable.
Bivariate analysis helps compare and control two or more related variables in situations where quality depends on the combine effect of these variables. This method is most useful when two different variables work together to affect the acceptability of a process or part thereof.
The bivariate analysis should be useful in supporting or failing to support the arguments of dependency theorists that there is an association between dependency and underdevelopment - The question of dependency and economic development: a quantitative analysis By Brian R. Farmer