Categorized Quantile-Quantile Plots - Advanced Tab

Graphical Analytic Techniques

Select the Advanced tab of the Categorized Quantile-Quantile Plots Startup Panel to create categorized Q-Q plots using a variety of distributions.

Layout. Select the type of layout for the graph(s).

Separate. Select this option button to produce a Separate plot layout (where each subset of cases is displayed in a separate graph) for the categorized plots.

Overlaid. Select this option button to produce an Overlaid plot layout (where all subsets are overlaid in one graph and identified by patterns and colors) for the categorized plots.

Variables. Click the Variables button to display a variable selection dialog box, in which you can select the X and (optional) Y grouping variables and the dependent variable(s) to be displayed in the graph. If more than one dependent variable is selected, then a sequence of graphs (one for each dependent variable) will be produced using the same set of grouping variables. The selections you make are displayed to the right of the Variables button.

Note that the selected grouping variables do not have to be categorical variables (e.g., contain codes); you can use one of the methods of categorization to categorize continuous variables. The selection of grouping variables is not necessary if the categories are defined via the Multiple Subsets option button.

Distribution. Select the desired theoretical distribution for this graph. Additional options available in this group box are dependent on the distribution selected. Specific parameters may be required for some of the distributions; when these distributions are selected, parameter options are displayed below the Distribution group box. Click the distribution links listed below for more information.

X-Categories / Y-Categories.  Categorization is used in two classes of graphs in Statistica: categorized graphs (e.g., Categorized Scatterplots) and graphs that include grouping or categorized variables (e.g., 2D Histograms, or 2D Box Plots).

Select Integer mode, Unique values, or Categories to specify that method of categorization for each of the variables selected via the Change Variable button, or use the Boundaries, Codes, or Multiple subsets options. For more information about each of these methods of categorization, click the links below:

Integer mode

Fitting line. The options in this group box pertain to the fitting line. Two types of fitting lines are available:

Display linear fit. When you select this check box, Statistica calculates and displays the linear fitting line. The equation of the linear fitting line (Y=a + bx, given in the third title of the resulting Q-Q plot) provides estimates for the Threshold (a, location) and the Scale (b) parameters of the specified distribution.

Custom fit. You can custom-define a fitting line to be included in the graph (in addition to the linear fit) by selecting the Custom fit check box and then entering user-defined Scale and Threshold (location) values. This is useful for comparing the linear fitting line (see above) with custom fitting lines based on known distributions in the family of distributions.

Note that both the linear fit and custom fit lines can be displayed in the graph (select both check boxes).

Adjustments. Use the options in this group box to adjust the values used in the determination of the theoretical quantiles: [(i - rankadj)/(n + nadj)] where i is the i'th ordered observation, n is the number of non-missing values and rankadj and nadj are user-defined adjustments to insure that this quantity is greater than 0 and less than 1, see below.

Ranks. Specify here the rank adjustment (rankadj; by default, .375), which is added to the ranks of the observed values when the theoretical quantiles are computed.

N. Specify here the sample size adjustment (nadj; by default, .25).

For more information, see Hahn and Shapiro, 1967.

Probability scale. Select this check box to scale the upper x-axis nonlinearly, according to the probability values given in the respective field (by default, .01, .05, .1, .25, .5, .75, .9, .96, .99). Vertical gridlines will be positioned along these percentiles. If this check box is cleared, no scale will be displayed on the upper x-axis.