PLOT MENU SUMMARY

The PLOTS menu allows you to generate individual plots of your data. The items of the menu generate plots whose nature is summarized here. For more information, choose a plot and then use the plot's help button.

HOLLOW-HISTOGRAM makes hollow frequency histogram plots (and frequency polygons or dynamic histograms) from raw data, based on frequencies calculated by binning values of a numeric variable. The formation of the bins is under the control of the user and may be changed dynamically via buttons on the plot. The plot cannot be linked to other plots.

DYNAMIC-HISTOGRAM makes dynamic frequency histogram plots (and frequency polygons or hollow histograms) from raw data, based on frequencies calculated by binning values of a numeric variable.  The formation of the bins is under the control of the user and may be changed dynamically via buttons on the plot. The plot cannot be linked to other plots.

LINKABLE-HISTOGRAM makes static frequency histogram plots based on frequencies calculated by binning values of a numeric variable. The plot consists of individual tiles which can be linked to other plots.

DISTRIBUTION-PLOT makes frequency distribution polygons (and dynamic or hollow histograms) from raw data, based on frequencies calculated by binning values of a numeric variable.  The formation of the bins is under the control of the user and may be changed dynamically via buttons on the plot. The plot cannot be linked to other plots.

CUMULATIVE-PLOT makes quantile plots and normal probability plots of numeric variables to show the shape of the data's cumulative distribution.

COMPARISON-PLOT makes quantile-quantile plots which can be used to compare the shape of the distribtions of two numeric variables.

DOT-PLOT makes a scatterplot of the first variable versus the observation sequence number. Dotplots can be used to determine if there is a relationship between a variable and the order in which it appears in the data. The two variables are represented by the X and Y axes. The observations are represented as points in the plot.

SCATTER-PLOT makes a scatterplot of the first two variables in the data. Scatterplots can be used to display the relationship between two variables. The two variables are represented by the X and Y axes. The observations are represented as points in the plot.

SPINNING-POINTS makes a three-dimensional spinnable scatterplot of the first three numeric variables in the data. Scatterplots can be used to display the relationship between variables. The variables are represented by the X, Y and Z axes. The observations are represented as points in the 3D space.

ORBITING-POINTS makes a six-dimensional spinnable scatterplot of the first six numeric variables in the data. Scatterplots can be used to display the relationship between variables. The variables are represented by the six axes. The observations are represented as points in the 6D space which are orbiting arround their centroid. Points which are close together in 6D space will have similar oribits.


LINE-PLOT makes a connected scatterplot of the first variable versus the observation sequence number. Line plots can be used to determine if there is a relationship between a variable and the order in which it appears in the data. The two variables are represented by the X and Y axes. The observations are represented as connected points in the plot.

BOX-PLOT makes boxplots from the numeric variables in your data. A boxplot is a schematic of a set of observations based on the variable's median and quartiles. The schematic can give you insight into the shape of the distribution of observations, and allows you to compare distribution shapes of different variables.

DIAMOND-PLOT makes diamond plots from the numeric variables in your data. A diamond plot is a schematic of a set of observations based on the variable's mean and standard deviation. The schematic can give you insight into the shape of the distribution of observations, and allows you to compare distribution shapes of different variables.

GROUPED BOX PLOT makes boxplots for each group in you data, using a categorical variable to form the groups and a numeric variable to form the boxplots. The boxplots can give you insight into the shape of the distribution of observations in each group, and allows you to compare distribution shapes of different groups.

BAR-GRAPH makes bar-graphs of as many as 4 categorical variables. The first several categorical variables are used. A bar graph consists of vertical bars whose height represents the frequency of crosstabulated categories of the data. Can create side-by-side frequency or probability bar graph of 1- to 4-way data, or stacked bar graph for 2- or 3-way data.

MOSAIC-PLOT makes mosaic plots of as many as 4 categorical variables. The first several categorical variables are used. A mosaic plot consists of tiles whose area represents the frequency of crosstabulated categories of the data.
