The *X-Y* scatter plot is one of the most powerful tools for
exploratory data analysis. GRAPHID includes a host of features to enhance the
basic scatter plot. These features are:

- Multi-window option for simultaneous plotting of several scatter
plots. This option allows the visualization of relationships between
several variables at a time, for example, the predictors of a regression
model to look for multicollinearity.
- Identification of cases in a scatter plot. This option is
particularly useful to identify the outlier cases.
*Regression lines*: Three different types of regression lines can be displayed on each scatter plot:

·
Local
regression

·
Local mean

·
Local median.

These are nonparametric regression lines, which are constructed through
smoothing with order statistics (k*-* nearest neighbor smoothing). The
number of neighbors is to be decided by the researcher.

- Histograms of variables can be plotted on the diagonal windows
of the multi-window scatter plot, to visualize the distributions of
different variables.
*Density plots*are essentially smooth versions of histograms. They provide smooth estimates of probability density curve. Order statistics can be used for constructing nonparametric density estimates. Let*i*be the number of points in a gate of width*r*corresponding to the point*X*(*i*) and let*I*(*i*) =*X*(*i*+*r*) –*X**( i*–*r*),. The density of the point X*i*) =*I*(*i*)/2*r.*