The data analysis program PrismCalc performs several types of functions on the data files produced by PrismView:
1.  Calculation of derivated parameters from the measured values, such as nearest neighbor distances and directions, surface and volume of three-dimensional particles, etc.
2. Plotting of a wide variety of graphic data presentations, including regression and scatter plots, and distribution histograms in many standard and specialized formats.
3. Basic descriptive statistics, classification and regression tools, and comparisons using both conventional and non-parametric statistical tools.
4. Comprehensive stereological measurement procedures using a variety of models for surfaces and thin sections.

You may use PrismCalc with the data files saved by PrismView. To illustrate the types of procedures that are available, you can use the file "Dendrites.Data" to perform the kinds of operations listed below. Feel free to experiment with other operations as well, or to apply similar methods to other data files.

1. After loading the file, create new parameters for each feature. Under the size menu, select Indent. Depth (the mean depth of indentations around the edge of the feature). Under the position menu, select Nearest N'bor Distance and Nearest N'bor Direction (the centroid-to-centroid geometry of nearest neighbors). Each of these parameters creates a new column in the data; each row corresponds to one of the separate features in the original image.

2. Plot the following relationships (in all cases, select the parameter from the scrolling dialog; except where noted, you can accept the default settings for the plots):
a. Regression plot of Equivalent Diameter (a measure of size) vs. Indent. Depth and against Mean Branch Length (measures of feature shape).
b. Distribution histograms of Length (the maximum dimension) and Formfactor (defined as 4 ¹ Area / Perimeter^2, a measure of shape). Then try a 2-Way Distribution of Length and Formfactor.
c. Rose Distribution of Nearest Neighbor Direction (select a plotting range of 0-360 degrees) to show anisotropy in the distribution.

3. Perform the following steps for statistical interpretation:
a. Compare the features on the left and right sides of the image by selecting Students t-Test with Equivalent Diameter as the analysis variable and X-Center of Gravity as the classification variable. The program reports that there is no signficant difference. Try the same thing with convexity (a measure of shape) as the classification variable, and the program reports that there is a significant difference (the convex particles tend to be small, and vice versa).
b. Repeat this comparison using the Kolmogorov-Smirnov test, which performs a nonparametric comparison.
c. Repeat this comparison using the Wilcoxon (Mann-Whitney) test, another nonparametric comparison. In order to do this, you must first perform the operation Rank by Variable and select Equivalent Diameter. This creates a new column with the rank values of each observation according to the selected variable. Then when you select Wilcoxon, you need only choose the classification variable.

4. Apply some stereological tools:
a. Estimate the size distribution of the three-dimensional objects revealed in the section image by selecting Saltykov.
b. Characterize the spacing of features by selecting Exner (the ratio of the mean of distances to a random distribution is greater than one, and that of the standard deviation is less than one, so these are self-avoiding features rather than being random or clustered).