The variable plotted on the horizontal, or X-axis, is called the predictor, independent or explanatory variable. the variable plotted on the vertical, or Y-axis, is called the dependent or response variable. These terms are often used in graphs plotting the results of correlation analyses and linear regression.
The terms are used in bivariate plots, with the scatterplot considered on of the most common plots. Mathematicians often use the term "independent" and dependent" in reference to the two types of variables because they do not necessarily imply cause and effect. The term "predictor" can lead to falsely interpreting the variable's ability to predict beyond the data's limits. "Explanatory" can also be misinterpreted by giving an impression of a causal effect between the two variable, when the data is only showing associations.
An example of the use of dependent and independent variables is the study of the association of birth weight and gestational age. Gestational age can be graphed on the x-axis as the independent variable, with birth weight on the Y-axis as the dependent variable. One possible result from the data is that there is a positive association between the two variables, with babies with a shorter gestational age more likely to weight less at birth and those with longer gestational ages to have higher birth weights..