A statistical variable is any set of observations in which the observations can be different. They need not be numeric or even ordered: for example, people's first names or the colour of cars. They can be ordered but still not numeric: for example, questions where you are asked to say whether you strongly disagree, disagree, are neutral, agree or strongly agree. Or they can be numeric, for example your age or height or a combination of your height and mass in the form of your BMI.
Essentially, it is any characteristic that can be "measured", and measured does not mean only in numeric terms.
what are the classification of variables
statistics
It measures associations between variables.
Sample statistics
There are many ways of categorising variables. One classification, used in statistics, is Nominal, Ordinal and Interval.
Explanatory and Response variables are just fancy words for independent and dependent variables. Explanatory is the independent variable and response is the dependent variable.
Sample Statistics
Analytical statistics
In statistics, bivariate data refers to data that comes with two variables.
Two or more explanatory variables are collinear when they have a linear relationship with each other. You are usually expected to remove at least one of the variables from your multiple regression analysis.
In statistics, regression analysis is a statistical process for estimating the relationships among variables. It includes many techniques for modeling and analyzing several variables, when the focus is on the relationship between a dependent variable and one or more independent variables.
The covariance between two variables is simply the average product of the values of two variables that have been expressed as deviations from their respective means. ------------------------------------------------------------------------------------------------- A worked example may be referenced at: http://math.info/Statistics/Covariance