When a distribution has two variables then it is called bivariate. For example, if we measure the income and expenditure of a certain group of persons-one variable will measure income and the other variable will measure expenditure and the values will form the bivariate distribution.

There may be any correlation between the variables, *i.e., *the change in one variable gives a specific change in the other variable. For example, if the increase (or decrease) of one variable results the increase (or decrease) of the other variable, then the correlation is said to be positive. If the increase (or decrease) leads to decrease (or increase) then the correlation is said to be negative.

The simplest way to represent the bivariate data in a diagram known as scatter diagram. For the bivariate distribution *(x,y), *the values *(x _{i}, y_{i}), i *= 1, 2, ...... ,

*n*of the variables are plotted in the xy-plane which is known as scatter diagram. This gives an idea about the correlation of the two variables.