Ribbon bar. Select the Graphs tab. In the More group, click 2D and from the menu, select Scatterplots to display the 2D Scatterplots dialog box.

Classic menus. From the Graphs - 2D Graphs submenu, select Scatterplots to display the 2D Scatterplots dialog box.

Two-dimensional scatterplots visualize a relation (correlation) between two variables X and Y (e.g., weight and height). Individual data points are represented in two-dimensional space, where axes represent the variables (X on the horizontal axis and Y on the vertical axis). The two coordinates (X and Y) that determine the location of each point correspond to its specific values on the two variables.

Numerous types of X-Y scatterplots are available: Regular, Double-Y, Multiple, Frequency, Bubble, Voronoi, and Quantile. Regular scatterplots are simple scatterplots of one set of X-Y variables. Double-Y plots involve one X variable and two Y variables. One Y variable is plotted against the left y-axis scale and one is plotted against a separate right y-axis scale. Different point markers are used for the two plots. Multiple scatterplots have one X variable and multiple Y variables. All Y variables are fit to a single y-axis scale, but each variable is represented on the graph by a different point marker. Frequency plots are regular X-Y scatterplots in which the size of point markers is proportional to the number of superimposed points at that set of X-Y coordinates. Bubble plots are regular X-Y scatterplots in which the size of point markers reflects the value of a third (weighting) variable. In Voronoi plots, the space between each plotted point marker on a regular scatterplot is divided by straight lines that define the areas surrounding each point such that any set of X-Y coordinates within the defined space is closer to its center point than to any other point. In Quantile scatterplots, the quantiles of the X variable are plotted against the quantiles of the Y variable. If the resulting data points fall on a straight line, the two variables follow the same distribution.

STATISTICA provides a variety of fit types for the graph: Linear, Polynomial, Logarithmic, Exponential, Distance Weighted LS, Neg Expon Weighted LS, Spline, and Lowess. Note that the selected function is applied to each set of X-Y variables (e.g., a Double-Y plot has two fit lines applied, one for each y-variable. Options to mark selected subsets of the data are available for Regular, Quantile, and Voronoi type plots.

See also, Conceptual Overviews - 2D Scatterplots.