An Overview of Aabel™ NG: NG2, v5 x64

Aabel™ NG, a New Standard of Data Analysis Design for Professional Users

Aabel NG Videos

Statistical Analysis

Interactive Graphing

Exploratory Analytics

User Guide eBooks

Features Summary

  • 64-bit throughout
  • Provides a highly modern GUI and unmatched integration of statistical/multivariate data analysis, exploratory analytics, scientific graphing & thematic mapping, data processing utilities, practical use and graphic quality.
  • An icon of power and modeless simplicity for professional users (modeless panels and windows do not block other activities of the application).
  • Distributed with three high quality PDF eBooks with over 1100 illustrations, providing a step-by-step guide for using the diverse features of the application, as well Quick Start Guide documentation for new users.
    • Simple design for accessing Stats Analyzer, Chart Designer, Graphic Organizer, and Interactive Filtering from the the same window, i.e., the graphic viewer:
    • Native worksheets allowing import of diverse data formats (including the SPSS .sav files), supporting diverse variable types (continuous and nominal numeric values, string, date, trend, dip, azimuth, longitude, latitude, easting, northing), providing numerous data management tools and other utilities, and enabling a rapid glance at distribution and descriptive statistics of different variables, range control of numeric data, and more
    • Modeless simplicity, now including over 95% of the application panels and windows
    • Support for exporting vector graphics (PDF and EPS) and bitmap formats (PNG, JPEG, JPEG 2000, TIFF, TIFF, GIF, BMP)
    • Interactive color management tools; choice of RGB vs. CMYK, creating and managing gradients
    • Continuous viewer pages, which makes it possible to generate any number of statistical output, view them by scrolling throughout the pages, use them for live presentation purposes, or export them using different options (including exporting all viewer pages as a single PDF document)
    • Graphic Organizer, a modeless panel with multiple important functions related to graphic contents of viewer pages
    • Numerous flexible customizing capabilities, majority of which modeless panels, updating any modification on the fly
    • Diverse document-independent data processing utilities including profile extractor, polygon data merger/data optimizer, trans-worksheet calculator, k-nearest neighbor and natural neighbor gridders, polynomial trend surface gridder, multi-worksheets sequential data merger, matrix cell-wise normalizer, matrix-to-matrix cell-wise operator, variable-based data transformer, 3D grid data processor, and 3D grid volume & area calculator:

Unique Data Pipeline Architecture

Advantages of Data Pipelines
What Are Data Pipelines?

Pipelines are data channels connecting the data sources (Aabel worksheets) (i) to graphic viewer data users (i.e., Stats Analyzer and Chart Designer), and (ii) to data processing utilities. Data pipelines have a unique design with many advantages:

  • You can perform graphing or statistical analysis from multiple Aabel worksheets, without a need to merge the data into a single worksheet.
  • You can have real-time interaction with data, e.g., change variables, change chart types, etc., all from within a single interface, and the results will be dynamically updated.
  • Created charts are not static graphics. They are hot-linked to the source worksheet(s) used to create the chart(s). If you make changes to source worksheet(s), the modifications will be dynamically updated on all charts using the data.
Powerful Exploratory Features

Data exploration in Aabel goes beyond data brushing. The pipeline architecture of the application has enabled the design of powerful and dynamic data exploration capabilities such as:

  • X-zooming (X for exclude), a tool with unique functionalities*
  • Performing multidimensional data filtering interactively (while performing exploratory analysis)

* X-zooming allows walking through hierarchies of numeric or categorical data rapidly, to (i) discover patterns and information that are otherwise masked, and (ii) extract data subsets from factorial levels of categorical data, or from numeric data, interactively.

Statistics and Multivariate Analysis Modules

ANOVA and ANCOVA (General Linear Model)

The GLM procedure allows the option of choosing dummy, effect, or orthogonal coding, and providing a simple and easy to use GUI.

  • ANOVA: Between-subjects design
  • Test of simple main effects for analyzing n-way interactions in between-subjects ANOVA
  • ANOVA: Within-subjects (repeated measures) design
  • ANOVA: Mixed between-within design
  • ANCOVA: Between-subjects design

Pairwise multiple comparisons accompanying between-subjects design include:

  • Tukey's HSD Test
  • Newman-Keuls (Neuman-Keuls) test
  • Tukey B Test
  • Fisher's LSD
  • Dunnett Test
  • Tukey-Kramer Test
  • Scheffé Test
  • Bonferroni-Dunn Test
  • Dunn-Sidak Test
  • Dunnett' C Test
  • Games Howell Test
Normality and Homoscedasticity Tests
Normality Tests
  • Shapiro-Wilk test
  • D'Agostino-Pearson test
  • Kolmogorov-Smirnov test (single sample)
  • Probability plot
Homoscedasticity Tests
  • Hartley's Fmax test
  • Bartlett's chi-square test
  • Levene test
  • Brown-Forsythe test
  • Cochran's C test
Non-Parametric Tests
  • Wilcoxon signed-ranks test
  • Wilcoxon matched pairs signed-ranks test
  • Mann-Whitney U test (Wilcoxon ranks sum test)
  • Kruskal-Wallis test
  • Spearman's rank-order correlation coefficient
  • Kendall's rank correlation coefficient (Kendall's tau)
  • Friedman two-way analysis of variance by ranks
  • Kolmogorov-Smirnov goodness-of-fit test for a single sample
Descriptive Statistics and Frequency Analysis
Descriptive Statistics
  • One-way descriptive statistics
  • n-Way descriptive statistics (generating tables from 2D slices)
  • Multifactor cell means
  • Weighted Arithmetic Mean
Frequency Analysis
  • One-way frequency analysis of categorical data
  • n-Way frequency analysis of categorical data
  • One-Way binning analysis of continuous data
  • Two-Way binning analysis of continuous data
Gaussian Kernel Density Estimate With AMISE Optimal Bandwidth

Gaussian kernel AMISE bandwidth analyzer:

  • Efficient use of Kernel density estimate, which is widely used in data mining and pattern recognition, depends on computation of the optimal bandwidth of the kernel. While AMISE (Asymptotic Mean Integrated Squared Error) optimal bandwidth can provide the best estimation, it involves extensive and time-consuming computation.
  • Gigawiz has developed a unique hybrid solver for processing the data and estimating the corresponding AMISE optimal bandwidth.
    • The Gigawiz hybrid solver has been stress tested using 10000 data sets, including both real world and simulated data.

Gaussian kernel density trace charts including:

  • A graph type whose plotting involves processing the data and computing the AMISE optimal bandwidth (using the Gigawiz hybrid solver) while generating the resulting chart on the fly.
  • A graph type with the rule of thumb bandwidth selectors (i.e., Silverman's approach and percentage of sample range), for exploratory visualization of the effect of bandwidth on kernel density estimation
  • Z-Score kernel density trace
Chi-Square Tests
  • The Chi-Square Goodness-of-Fit Test (this test, also referred to as the χ2 test for a single sample)
  • The Single-Sample Chi-Square Test for Population Variance
t-Test, F-Tests, z-Test
  • Single samples t-test
  • Paired samples t-test
  • Unpaired samples t-test
  • F-test
  • Paired samples z-test
  • Unpaired samples z-test
Correlations (Bivariate)
  • Correlations and covariance matrices
  • Correlation matrix with pairwise significance test
  • Pearson product-moment correlation coefficient (Pearson r)
  • Fisher's z transformation (zr)
  • Spearman's rank-order correlation coefficient (Spearman's ρ)
  • Kendall's rank correlation coefficient (Kendall's τ)
Dissimilarity and Distance Matrices
  • Bray-Curtis and Zero-Adjusted Bray-Curtis Dissimilarity
  • Correlation Coefficient Dissimilarity
  • Euclidean and Manhattan Distance Measures
Contingency Table Analysis
  • Two-Way Contingency Tables
  • Two-Way Tables of Cell Descriptive Statistics
Internal Consistency Reliability

Aabel provides the following methods for internal consistency reliability estimates:

  • Cronbach's alpha
  • Kuder-Richardson rho (Formula 20)
  • Kuder-Richardson rho (Formula 21)
Survival Analysis and Cox Regression

The survival analysis includes:

  • Kaplan-Meier survival analysis
  • Nelson-Aalen survival analysis
  • Cox proportional hazard regression

Survival analysis charts include:

  • Kaplan-Meier and Nelson-Aalen charts, with option of plotting the survival curves With 95% pointwise confidence intervals
  • Cumulative hazard rate chart
  • Hazard ratio chart
  • Cox regression chart
Regression Analysis of Bivariate Data

In addition to curve fitting methods avaiable in the Chart Designer panel, analysis of built-in regression methods* in the Stats Analyzer enables:

  • Storing the predicted and residual values in source worksheets
  • Testing normality of the regression residuals (when appropriate).
  • Storing the cubic spline interpolation output in a source worksheet

* The regression types include: Y on X, linear major axis, linear, reduced major axis, polynomial, exponential, logarithmic, power, cubic spline.

Receiver Operating Characteristic Curves (ROC)
  • ROC for a single test
  • ROC for two tests on paired samples
  • ROC for two tests on unpaired samples
Trend Surface Analysis
  • Polynomial trend surface analysis of XYZ data
  • Polynomial trend surface analysis of matrix data
Multiple Regression
  • Multiple regression with numeric predictors
  • Multiple regression with categorical predictors

Output from the multiple regression analysis can include:

  • The Correlation Matrix of Predictors (specific to analysis with numeric predictors)
  • Collinearity diagnostics (specific to analysis with numeric predictors)
  • Predicted and residual values
  • Multiple regression coefficients and model summary report
  • ANOVA for the significance of full model regression
  • ANOVA test report for contribution of individual predictors to the model
  • Normality tests on regression residuals
Canonical Correlation Analysis

The canonical output can include:

  • The correlation matrix of observed variables
  • Canonical correlation results, including correlation summary and multivariate significance tests
  • Eigenvalues
  • Canonical coefficients (weights) and structure coefficients
  • Canonical scores
  • Redundancy analysis
  • D'Agostino-Pearson teston observed variables and canonical scores
Principal Component Analysis (PCA)

The PCA output can include:

  • Correlation or covariance matrix
  • Bartlett's test of sphericity
  • Partial coefficient matrix
  • Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy
  • Eigenvalues and PC loadings
  • PC scores
Factor Analysis
  • R-mode factor analysis
  • Q-mode factor analysis

The R-mode factor analysis output can include:

  • Correlation matrix of the original data
  • Bartlett's test of sphericity
  • Partial coefficient matrix
  • Kaiser-Meyer-Olkin (KMO) measure of sampling adequac
  • Reproduced and residual correlation matrices
  • Loadings and communalities for extracted factors
  • Factor scores
Hierarchical Cluster Analysis

The agglomerative methods in Aabel NG include:

    • Single Linkage (Nearest neighbor)
    • Complete Linkage (Furthest Neighbor)
    • McQuitty's Method (WPGMA)
    • UPGMA: Average Linkage Between Groups (Unweighted)
    • Gower's Method (Median)
    • Ward's method
    • Centroid Method
K-Means Cluster Analysis

K-means clustering allows analyzing inter-object relationship in multidimensional space, and is used for clustering/grouping data objects with similar characteristics.

  • You can define the number of clusters to be generated with the following limitation: K < n.
  • Aabel uses the method of Hartigan and Wong (1979), performs several random starts, and attempts to converge to a global minimum of the squared error distortion.
Outlier Analysis
  • Mahalanobis Distance
  • Jackknifed Mahalanobis Distance
  • Exploratory outlier analysis chart:
    • This graph type allows (i) classifying zones that include groups of objects with different range of Mahalanobis distance below the outlier zone, and (ii) generating subsets of data from different zones for further analysis.
Partial Least Squares Regression (PLS)

The PLS method implemented in Aabel (i) uses principal component analysis (PCA) to derive the prediction functions from factors calculated from cross-product matrices involving both Y and X variables, and (ii) allows predicting one or more dependent variables from a set of independent (predictor variables).

  • PLS performed on a single data set (as for multiple regression)
  • Using a training data set for predicting unknowns, new events, etc.
Logistic Regression

Logistic regression allows you to predict a discrete outcome from a set of independent variables that may be continuous, discrete, or binary. The dependent variable is binary/dichotomous/binominal.

The method includes probability and logit (probability), and alllows generating:

  • Probability plots with multiple dimension projections
  • Probability plots with one independent variable
LOWESS (Robust Locally weighted Regression) With Weighted CI
  • LOWESS is an outlier resistant, robust locally weighted regression and scatter smoothing, in which the fitted value of xk is the value of a polynomial fit to the data using weighted least squares, where the weight for (xi, yi) is large if xi is close to xk and small if xi is far from xk.
  • The features and graph types include:
    • Exploratory LOWESS Charts
    • LOWESS Residual Dependence Graph
    • Adding Weighted Confidence Interval (CI) to LOWESS Curves
    • Using the LOWESS of Residuals as a Diagnostic Tool*

* The residual plot can provide information for choosing a reasonable value for the local smoothing width).

Univariate & Multivariate Statistical Charts

Parallel Coordinates

Parallel coordinates are designed to represent multidimensional information and provide a tool for visualizing multivariate relations.

This graph category provides the following graph types:

  • Exploratory parallel coordinates
  • Binned density-based parallel coordinates
  • Sigma- or CI-based parallel coordinates
  • Factorial parallel coordinates
Basic & Exploratory Heatmaps
  • Exploratory Heatmap with:
    • Hierarchical clustering methods
    • Principal component analysis (PCA)
  • Basic Heatmap allowing:
    • Optional scaling of matrix cell-values
    • Representing cell values using a circular-shaped or square-shaped frame insert
Statistical Quality Control Charts

Shewhart control charts for variables:

  • Xbar (R) chart
  • Xbar (S) chart
  • R chart
  • S chart

Other control charts for variables:

  • Levey-Jennings chart (quality control of laboratory measurements)
  • Individual measurements
  • Moving range chart

Shewhart control charts for attributes:

  • p chart
  • np chart
  • c chart
  • u chart

The Westgard multi-rules procedure and Western Electric Company (WECO) warning rules can be optionally applied to the appropriate quality control charts.

Data Screening Charts
  • Exploratory outlier analysis chart
  • Factor scree plot
  • Factor cumulative (%) variance chart
More Information
Data Screening Charts
Histograms of Continuous and Categorical Data
  • Univariate histogram of continuous data
  • 2D histogram of continuous data
  • Multi-profile histograms
  • Categorical histogram
  • Pareto chart
  • Ogive chart
  • Spine chart
Q-Q and Probability Charts
  • Quantile-quantile Chart
  • Normal probability
  • Uniform probability
Frequency Dot Plots
  • Single sample frequency dot plots
  • Parallel-axes dot plot of paired samples/repeated measures
  • Parallel-axes dot plot of unpaired samples
Box & Whisker Charts

    Box & whisker chart types include:

  • One-way box & whisker
  • Two-way box & whisker
  • Three-way box & whisker
Box-Percentile Charts

    Box-percentile chart types include:

  • One-way box-percentile
  • Two-way box-percentile
  • Three-way box-percentile
Violin Charts

    A violin chart comprises a combination of box plot and density trace; violin chart types include:

  • One-way violin
  • Two-way violin
  • Three-way violin
  • Bandwidth Selector Options:

  • For interactive, exploratory visualization, you can choose one of the following options:
    • Silverman's approach using alpha
    • Silverman's approach using IQR
    • Percentage of sample range (for this option, you can obtain the AMISE optimal bandwidth estimate (as well as the corresponding scaling factor) in the Stats Analyzer and use the output for providing the user-defined scaling factor)
Mean Bar Charts
  • One-way bar Chart
  • Two-way bar chart
  • Three-way bar chart
  • Error bar options include standard error of mean, standard deviation, confidence interval (90%, 95%, 97.5%, 99%)
More Information
Mean Bar Charts
Mean line and Interaction Charts
  • Two-Way Interaction Chart (Two-Way Stacked Mean line Plot)
  • One-Way Mean line Chart
  • Error bar options include standard error of mean, standard deviation, and confidence interval (90%, 95%, 97.5%, 99%)
Diamond Mean Comparison Charts
  • One-way diamond mean comparison chart
  • Two-way diamond mean comparison chart
Mosaic, Parquet, and Chessboard Diagrams
  • Mosaic diagram (observed frequencies)
  • Parquet diagram (expected frequencies)
  • Mosaic (Goodness-of-Fit Statistics)
  • Mosaic Diagram Arranged by Categories
  • Parquet (Matrix of Expected Frequencies)
  • Chessboard Diagram (Magnifying Missing Data)
Bland & Altman Difference Plots

The Bland & Altman method for comparing two methods of measurement or two paired variables; the confidence interval display options include:

  • ±1.96 standard deviation
  • Paired t-test CI (95%)
  • Paired t-test CI (99%)

Thematic Maps and Map Projection Utilities

Import Capabilities and Thematic Maps
Import Capabilities
  • ArcView shape files and associated dBase files
  • Formats provided by the USGS Coastline Extractor:
    • Arc/Info Ungenerate
    • Mapgen and Matlab
    • Splus
Thematic Map Diagrams
  • Thematic map of continuous data
  • Thematic map of categorical data
  • Thematic symbol chart
  • Thematic contour of matrix data
  • Thematic heatmap
  • Thematic XY point frequency chart

A Thematic Map of World Press Freedom Ranking (2016): Compiled by Reporters Sans Frantières (

Thematic Map of 2016 World Press Freedom Ranking

Map Projection Utilities (Coordinate Transformations)
  • Geographic
  • Albers Conical Equal Area
  • Azimuthal Equidistant
  • Equidistant Conic
  • Gnomonic
  • Hammer
  • Interrupted Goode Homolosine
  • Lambert Conformal Conic
  • Mercator
  • Miller Cylindrical
  • Mollweide
  • Orthographic
  • Polar Stereographic
  • Polyconic
  • Robinson
  • Stereographic
  • Transverse Mercator
  • Universal Transverse Mercator (UTM)
  • Van der Grinten

Specialized Scientific Graphing

Wind Rose Module (Using Raw Wind Data)
  • Wind rose projects a large quantity of data in a simple graphical plot that summarize the occurrence of winds, showing their speed, direction and frequency in a polar coordinate grid.

Wind Rose Diagram

Structural Diagrams
  • Stereographic scatter
  • Stereographic point density contour
  • Full circle structural rose with area of the petals proportional to the frequency, symmetric or asymmetric
  • Full circle structural rose with length of the petals proportional to the frequency, symmetric or asymmetric
  • Half circle structural rose with length or area of petals proportional to the frequency
  • Full circle structural lineament, symmetric or asymmetric
  • Half circle structural Full circle lineament

Structural Data: Stereographic Projections of Directional Data

Structural Data: Eigenvalues Summary Statistics

REE (Rare Earth Elements), Multi-Elements Spidergrams
  • A specialized module for generating n-dimensional spidergrams (geospider diagram) for comparing abundance of REE or multi-elements of an analyzed rock sample normalized to their abundance in type-rocks.
  • Aabel is distributed with a plot definitions library that includes 30 spidergram reference plot definitions for representing geochemical data.
  • Specialized group-based REE or multi-elements spidergrams include:
    • Group-based n-dimensional spidergrams differentiated by data object markers and/or line attributes
    • Group-based REE / multi-elements Bands
  • The group-based diagrams provide flexibility for exploratory visualization of spidergrams generated from large data sets.
Sequence Alignment Diagram
  • This diagram is designed to plot genomic sequence alignment by mapping query sequences to target sequences.
  • Includes four plot types
  • Stepwise X-zooming allows exploring the sequence alignment data
More Information
Sequence Alignment Diagram
CCG Diagrams (Combination Column Graphs)
  • This diagram is designed to permit a combination of column graphs that reflect variation against sorted values (in an increasing order) of a common Y-axis. It is hence ideal for plotting variations against depth, time, or similar variables.
  • The automatic sorting of the data will take place in the Visualization & Statistics pipeline, without changing the order they are stored in the data source.
  • Each column of a CCG diagram can include either a single variable or multiple variables.

General Purpose 2D, 3D, Matrix, Ternary, Voronoi, Bubble, and More

2D Scatter, Clustered Rays, Convex Hulls, Cross-Axes, and Series Charts
  • XY scatter chart with important exploratory features
  • XY clustered rays connected mean or median of the groups
  • XY convex hulls of groups
  • Cross-axes XY scatter
  • Scatter series charts, including:
    • Scatter series sort by X values
    • Scatter series across X categories
    • Double-Y scatter series sort by X values
Scatter-Line Combination Charts
  • XY Scatter-line combination charts*:
    • With data objects connected along the sorted values of Y-axis
    • With data objects connected along the sorted values of X-axis

    * Why Combining XY scatter and Line Chart Properties?

    • In an XY scatter chart, the data points represent groups of data objects that are plotted in the pipeline order (i.e., the order they are stored in the worksheet)
    • In a line chart, the data points represent variables plotted along the sorted values of the Y- or X-axis.
    • Combination graph types enable plotting a line chart in which the data points represent groups of data objects.
  • Multi-profile scatter-line charts:
    • Trends of multiple X-variables plotted across the sorted values of a common Y-axis
    • Trends of multiple Y-variables plotted across the sorted values of a common X-axis
Matrix of Scatter, Clustered Rays, Convex Hulls, and Area Charts
  • Matrix of XY scatter graphs
  • Matrix of clustered rays connected mean or median of the groups
  • Matrix of convex hulls of groups displaying the group boundaries and the amount of overlap in a multivariate set of data
  • Matrix of XY (value-axes) area graphs
3D scatter, 4D Scatter, and 3D Spinning Charts
  • 3D scatter
  • 4D scatter (displaying a 4th dimension using a color scale)
  • 3D spinning chart (this graph type is suitable for exploratory pattern recognition in multivariate data)

These 3D charts allow continuous rotation (360 degrees).

Ternary Scatter and Ternary Bubble Charts
  • Ternary scatter:
    • Supporting ternary zooming
    • Having ability to draw the plot clockwise or counterclockwise
    • Having the option of displaying error regions
  • Ternary bubble*

* A ternary chart displaying a 4th dimension whose values are shown by bubbles using a continuous color scale.

2D Contour Charts
  • 2D Contour of matrix data* using binned scale
  • 2D Contour of matrix data* using continuous scale
  • Contour of XYZ data using binned scale, contouring by triangulation

* For generating matrix data from XYZ data, you can use k-nearest or natural neighbor gridder or polynomial trend-surface gridder utilities.

3D Surface and 3D Mesh Charts
  • 3D contoured surface requiring matrix data*
  • 3D mesh (wire frame) requiring matrix data*
  • 3D XYZ Contour Points, contouring by triangulation

* For generating matrix data from XYZ data, you can use the k-nearest neighbor, natural neighbor, or polynomial trend-surface gridder utility.

Voronoi Diagrams (Thiessen or Dirichlet Polygons)
  • The Voronoi diagram subdivides the X-Y space of the chart into polygons surrounding each data point. These polygons represent the most compact division of space possible.
  • Voronoi diagram is particularly suited for studying the area of influence of each point.
  • The chart types include:
    • Standard Voronoi
    • Polygons color coded by values of a third variable
    • Group-based voronoi
Waterfall Charts

Waterfall charts are ideal for comparing variations between multiple data sets that are obtained under similar conditions. The chart types include:

  • Waterfall line series
  • Waterfall area series
  • Waterfall pseudo-surface
Spider Charts

Spider charts (also known as radar charts) display variations in multiple data series that represent the same factors. The chart types include:

  • Stacked area spider with option of using individual, individual normalized, or equal scaling of spokes
  • Line spider chart with option of using individual or equal scaling
  • Line spider with option of using percentage data or transforming data into 100% values during plotting
  • Filled spider chart with option of using individual or equal scaling
Polar Charts

Polar charts can be used to display non-directional data series (e.g., data representing speed) against variation in angles. The values of the non-directional data will be plotted proportional to the radius of the polar chart.

  • Polar stacked-area/-petal series
    • Polar stacked-petal series chart is not a substitute for wind rose diagram. To summarize and represent the wind data, see the Wind Rose Module.
  • Polar scatter series
  • Polar line series
Bubble Charts
  • Standard bubble chart supporting regression
  • 4D Bubble Chart (4th D Color-Coded)
  • Group-based bubble chart* supporting regression by group

* The bubbles belong to different groups of data object are differentiated by the source worksheet rows marker colors.

Line Series Charts
  • Line series sort by X values
  • Line series across X categories
  • Run sequence
  • Multiple paired XY line series
  • Double-Y line series sort by X values
  • Double-Y line series across X categories
Column Charts
  • Column and stacked column charts, including:
    • Single variable column chart
    • Stacked and 100% stacked column charts
    • XY (value-axes) column and stacked column charts
  • Clustered column chart (side-by-side columns)
  • Column-line combination chart*
  • Multi-profile column charts (stacks of column charts)

* The combination graphs share the same category axis, but can have the same or separate value axis.

Bar Charts
  • Bar and stacked bar charts, including:
    • Single variable bar chart
    • Stacked and 100% stacked bar charts
    • XY (value-axes) column and stacked bar charts
  • Clustered bar chart (side-by-side bars)
  • Bar-line combination chart*

* The combination graphs share the same category axis, but can have the same or separate value axis.

Area Charts
  • Area and stacked area charts, including:
    • Single variable area chart
    • Stacked and 100% stacked area charts
    • XY (value-axes) column and stacked area charts
  • Area-line combination charts*
  • Multi-profile area charts

* The combination graphs share the same category axis, but can have the same or separate value axis.

3D Column, Area, and Band Charts
  • 3D column
  • 3D area
  • 3D band
XY Scatter Pie and Standard Pie Charts
  • XY scatter pie chart*
  • Standard pie chart

* Displaying pies on an XY chart, where the center of each pie has a unique XY coordinate.

Stacked Bubble Charts
  • Stacked (univariate) bubble chart
  • XY scatter stacked bubble chart*

* Displaying stacked bubbles on an XY chart, where the center of each stacked bubble has a unique XY coordinate.

Stock (H-L-O-C) and High-Low Charts
  • Stock charts (candlestick and bar) with the option of displaying Bollinger band
  • High-low bar and column charts
  • XY (value axes) high-low bar and column charts
Vector Charts
  • XY vector using h and v vector components
  • Matrix (gridded) vector)
  • XY vector

Applying Error Bars and Curve Fitting

Error Bars

Adding error bars to charts allows a graphical display of the statistical probability of errors, the experimental and analytical errors, the data outliers, etc. You can choose to apply the error bars defining them symmetrically or asymmetrically.

Error bars defined for individual variables can be applied to:

  • XY scatter chart
  • Scatter series charts
  • Matrix scatter
  • Line series charts
  • Column charts
  • Bar charts
  • Area charts
  • Mean bar and interaction charts

Ternary error regions can be applied to:

  • Ternary scatter charts
Curve Fitting
Pre-Defined Functions
  • Linear (X on Y)
  • Linear (thru zero)
  • Major axis
  • Reduced major axis
  • Polynomial
  • Exponential
  • Logarithmic
  • Power
  • Cubic Spline interpolation
User-Defined Non-Linear Curve Fitting Module


  • A library of functions
  • An interactive interface

Aabel NG Graphic Viewer Features

Summary of Graphic Viewer Features

The graphic viewer is the Aabel interface for:

  • Data visualization & charting
  • Exploratory data analysis
  • Displaying the output (tables and/or graphs) from statistical analysis
  • Accessing different panels for performing analysis and customizing graphics

In a graphic viewer document, you can:

  • Use a single page or continuous pages
  • Export all pages as PDF in a single document

The graphic viewer data analysis and graphing panels include:

  • Stats Analyzer
  • Chart Designer
  • Graphic Organizer

Data management and customizing panels include:

  • Filter panel
  • Data Pipeline Controller
  • Curve fit and error bars panels
  • Axis and Legend panels, etc.

Aabel NG Graphic Viewer Header and Contextual Bar Controls

Access to Graphic Viewer Panels

Stats Analyzer: Simplicity at Your Finger Tips
  • Aabel NG Stats Analyzer has a modern interface, designed to provide flexibility and ease of use; it allows performing different analyses from the same or different worksheet sources without the need to create a different viewer for each method.
  • The graphs and tables generated by statistical methods and multivariate data analysis will be displayed on the viewer page(s).
  • The viewer filters, if activated, will be available to Stats Analyzer.
  • Many methods allow storing the results in auto-generated worksheets that can be used for follow-up analysis, etc.

Stats Analyzer

View a short video showing the ease of use of the Stats Analyzer controls for performing statistical analysis:

Chart Designer: Visual Analytics at Its Best
  • Chart Designer panel from within a single interface provides controls for:
    • Selecting and plotting different graph types
    • Choosing the required variables and plot options (When modifying variables or/and plot options of an existing graph, the changes will dynamically be updated on the graph)

Chart Designer

View a short video showing the ease of use of the Chart Designer controls for creating different graph types:

Graphic Organizer

Graphic Organizer panel displays a list of all graphics of the viewer page in focus, and allows:

  • Selecting objects (useful for selecting objects positioned behind other objects on the viewer page)
  • Changing the stacking order of objects
  • Hiding, locking, or deleting objects
  • Modifying size of any object by defining exact dimensions
  • Modifying the opacity of fills, lines, and markers of 2D charts
  • Applying X-zoom to exclude data from a given chart without affecting other charts using the same data source(s)
  • Hiding/showing chart legends and 2D chart axes
  • Alternative means of activation an inactive chart pane

Graphic Organizer

Filter Utility: Multi-Dimensional Data Filtering
  • If you are working with a wide range of data but are only interested in a subset based on specific criteria, the Aabel data filtering tools can be used to limit data to your criteria.
  • Aabel data filtering is comparable to database searches; furthermore, the results of data filtering can be dynamically updated on charts currently using the data to which an active filter is applied.
Worksheet Filter Utility vs. Graphic Viewer Filter Utility
  • Worksheet Filter Utility allows creating filter or extracting subsets of data from a single worksheet.
  • Graphic viewer Filter Utility provide the following abilities:
    • Allows extracting subsets of data from multiple worksheets that are the data members of a Visualization and Statistics Pipeline
    • Can be used to filter regions of data according to data patterns
    • Can be used for interactive filtering and hence for data exploration
Graphic Viewer Data Pipeline Controller

The Visualization & Statistics Pipelines have important user-controlled functions, providing flexibility for:

  • Viewing how many pipelines are transmitting data to a viewer
  • Viewing which pipeline is the viewer active pipeline
  • Viewing the list of worksheet members of viewer data pipelines
  • Creating new pipelines in an existing viewer document
  • Deleting an inactive pipeline

Data Pipeline Controller

Graphic Viewer Text Editor and Table Stylizer
    Text Editor and Table Stylizer
  • The table stylizer is provided for (i) editing the auto-generated tables that are part of the statistical methods output, and (ii) creating tables.
  • The text editor allows creating/editing multiple-line text, and provides Rich Text and Unicode support.
    Unicode Support
  • Aabel supports Unicode for storing data in worksheets, for graphing data, and for creating tables and text frames.
  • Ranking of categorical data is based on the US English writing system to ensure consistency in statistical outputs independent of the machine language settings.
Graphic Viewer Appearance Panel

Appearance panel provides controls for applying and modifying background fill (color or gradients) to specific objects, including:

  • Adding background to charts contained within the axis lines
  • Adding background to objects drawn using tools from the viewer toolbar
  • Adding background to any test box or table
  • Controls for customizing stroke attributes of selected objects
  • Controls for defining an arrowhead for straight lines or polylines
Graphic Viewer Color Theme Designer
  • Aabel graphic viewers use a white background, and drawings of chart axis, ticks and grids, axis labels and titles will initially be black (which can be modified using the controls in the Axis and Legend panels)
  • The color theme designer allows creating and storing user-defined color themes, where for each theme you can define:
    • A background (solid) color or gradient for the viewer pages
    • Colors for different chart elements, text box and table fonts, strokes and fills of graphic objects
Format for Exporting and Copying Graphics
  • Vector images:
    • PDF
    • EPS
  • Bitmap formats:
    • PNG
    • JPEG
    • JPEG 2000
    • TIFF
    • GIF
    • BMP
  • PDF (the images copied into the clipboard will be PDF)

Does Aabel Honor the Gradient Opacity During Export?

During export or copying, Aabel honors opacity applied to gradients (whether the opacity of the gradient is uniform or defined differently for each color).

View Examples of Exporting or Copying Aabel Graphics

Worksheet Features

Supported Data Import Formats
  • SPSS.sav files*
  • Excel format: 95, 97-2004 workbook (.xls)
  • Delimited text data (tab, comma, semicolon, space, etc.)
  • Fortran formatted data
  • Delimited numeric matrix data
  • Binary numeric matrix formats (8 bit, 16 bit, 32 bit, and 64 bit data)
  • dBase (II, III, IV) formats
  • ArcView shape files (and associated .dbf and .shx files)
  • Arc/Info Ungenerate
  • Mapgen
  • Matlab
  • Splus (2-Column ASCII)

* Sav importer has the option of importing the .sav file labels both for cell values and variable names.

Supported Variable Types
  • Continuous numeric
  • Nominal
  • String (with Unicode support)
  • Longitude, Latitude
  • Easting, Northing
  • Trend
  • Dip/Plunge
  • Azimuth
  • Date formats (pre-defined and custom design):
    • Having a range of 500,000 B.C. to 80,000 A.D
    • Using a Julian Calendar from January 4713 B.C. to October 1582, and then switching to the present Gregorian Calendar
    • Having a resolution of one millisecond from the first of January 4713 B.C. to 80 000 A.D., and one year between 500 000 B.C. to January 4713 B.C.
The Worksheet Data Management Tools
  • Multidimensional data filtering tools for generating subsets of data
  • Sorting worksheet data with a single or multiple keys
  • Transposing data
  • Pivoting and summarizing multidimensional data (cross tabulation)
  • Cross-interpolation
  • Merging multiple textual data columns into one column
  • Merging numeric or textual data without concatenating
  • Recoding string values on a one-to-one basis
  • Recoding multiple string values to a single value
  • Recoding nominal number values to corresonding string values
  • Recoding continuous data to categories representing data ranges
  • Reordering rows and columns
  • Pivoting and summarizing multidimensional data
  • Splitting and pivoting raw data
  • Stacking data columns
  • Cross interpolation
  • Assigning markers to groups of data objects using levels of a categorical vatiable
  • Generating a categorical variable from unique object markers
  • Generating marker codes from object markers (
  • Variable finder panel (provided for rapid scanning through data columns in a worksheet with large number of variables or for bringing a specific data column into the field of view)
Built-in Worksheet Calculator
  • Provides 46 pre-defined mathematical and statistical functions
  • Includes Boolean/conditional operators
  • Provides functions that operate on variables by indices instead of names
  • Allows addressing the worksheet cells explicitly
  • Provides assign and calculate commands for applying the same formula to multiple columns
The Worksheet Notebook
  • It displays a list of all variables present in the worksheet
  • It provides a text area for storing notes such as data source references or other information
  • The worksheet notebook further stores important information regarding some of the analysis, data filtering, etc.
More Information
The Worksheet Notebook

Data Processing Utilities

Open-GL Based 3D Grid Data Processor Utility

    This Open-GL based utility allows exploring single or multiple grid(s) and performing the following data processing, the results of which can be stored in an auto-generated worksheet for further analysis or graphing purposes. The functions include:

  • Subtracting a grid Z-values from another (e.g., generating a grid for an isopach map)
  • Subtracting a grid Z-values from a user-defined XY plane
  • Subtracting a user-defined XY plane from a grid Z-values
  • Multiplying a grid Z-values by a constant, e.g., converting the Z-values from feet to meter
  • Resampling the displayed grid by user-defined number of grid cells along the X and Y coordinates; e.g., for increasing resolution of a grid for volume or area calculations.
3D Grid Data Processor Utility
Open-GL Based 3D Grid Volume and Area Calculator Utility

    This utility allows calculating a number of parameters from a matrix either by applying the calculations to a user-defined polygon path comprising straight segments, or to the total data coverage.

  • The output corresponding to the user-defined polygon path includes:
    • 2D area within the defined path
    • Surface area within the defined path
    • Positive volume with the defined path (i.e., the volume calculated for the Z-values above zero
    • Maximum Z-value within the defined path
    • Minimum Z-value within the defined path
  • The output corresponding to all available data in the source worksheet includes:
    • 2D area
    • Surface area
    • Positive volume
    • Negative volume
    • Maximum Z-value
    • Minimum Z-value
k-Nearest Neighbor, Natural Neighbor, and Polynomial Trend-Surface Gridders
  • k-Nearest Neighbor and Natural Neighbor Utility allows:
    • Creating a continuous surface from an unevenly spaced XYZ data set
  • Polynomial Trend-Surface Utility allows:
    • Creating trend surfaces from XYZ data to derive a continuous smooth surface from irregular data, or isolate regional trends from local variations

Gridding Irregularly Spaced XYZ Data to a Regularly Spaced Matrix

k-Nearest Neighbor, Natural Neighbor, and Polynomial Trend-Surface Gridding

Profile Extractor Utility
  • This utility can be used for extracting a profile from a matrix by:
    • (a) Defining a path comprising straight segments
    • (b) Generating a worksheet to store the length and the corresponding Z values of the defined profile at control points

Extracting a Profile From Matrix Data

Polygon Data-Merger/Data-Optimizer
  • This utility allows:
    • Merging polygons into a single polygon allows generating spatial mask data required for plotting thematic contours or thematic heatmaps
    • Optimizing polygon data for reducing the file size of worksheets storing polygon coordinate data significantly

Utility for Generating Spatial Mask Data

Multi-Worksheets Sequential Data Merger Utility
  • This utility allows:
    • Merging data from multiple worksheets
    • Generating a new worksheet in which the sequentially merged data are placed

Sequential Data Mergering

Matrix Cell-Wise Operator Utilities
  • These utilities include:
    • Matrix-to-Matrix Cell-Wise Operator (this must not be confused with matrix arithmetic)
    • Matrix Cell-Wise Normalizer

Matrix cell-Wise Operations

Variable-Based Data Transformer Utility
  • This utility allows performing variable-based data transformation.
  • Transformations include standardize, normalize, logarithmisize (four options), log center, mean center, square, square root, ranking variables individually, ranking variables jointly.
Trans-Worksheet Calculator Utility
  • In addition to the built-in worksheet calculator that allows calculations within a single worksheet, Aabel provides a utility (Trans-Worksheet Calculator).

Why having two calculator utilities?

  • As outlined below, each calculator utility has different capabilities and limitations, which are specific to requirements of the task to be performed.

Utility for Generating Spatial Mask Data

Trans-Worksheet Calculator
  • Can be used for calculating formulas across multiple worksheets that are members of a data processing Pipeline.
  • Will honor the on/off (checked/unchecked) state of the source worksheet object links.
  • Can not use variable indices (instead of variable names) for calculations, and can not address worksheet cells explicitly.
  • Does not provide functions that are dependent on number of objects/cases.
  • Does not allow assigning the same formula to multiple worksheet columns.
Built-in Worksheet Calculator
  • Can be used for calculating formulas only within a given worksheet.
  • Can not honor the on/off (checked/unchecked) state of the source worksheet object links.
  • Can use variable indices (instead of variable names) for calculations, and can address worksheet cells explicitly.
  • Provides functions that are dependent on number of objects/cases.
  • Allows assigning the same formula to multiple columns.

Customizing Panels for Data Representation

Color Management, Color Picker Pane, and Color Editor
  • Aabel uses RGB and CMYK color models.
  • Color picker pane has 256 color swatches, each of which can be customized independently.
  • Color picker pane is present in worksheets, the graphic viewer, and all chart customizing panels, allowing to choose or modify colors of markers, lines, fills, contours, color-coded tables, text, etc.
  • The conversion between different color models can be based on the System- or user-installed profile.
  • The color editor allows creating, customizing, storing, and using color arrays for mapping data ranges to color scales.
High Quality Vector/Stencil Patterns
  • These patterns can be used for generating high quality 2D graphics for B & W publications or in combination with any color.
Aabel Symbols and Unicode Glyphs

For representing data points, the graphic viewer panels provide:

  • Aabel symbols: A palette with 175 marker symbols, each of which can be scaled from 50 to 200% of the initial size (100%) in 20 steps
  • Unicode glyphs/symbols: A palette that holds 176 Unicode characters/symbols/glyphs is available for data representation; each item in this palette can be replaced by a Unicode character/glyph from the System character palette, and can be scaled from 50 to 200% of the initial size (100%) in 20 steps
Tools for Customizing Chart Legends and Legend Entries

A wide variety of customizing controls are avaiable, including:

  • Tools for customizing legend keys (markers, lines, color or pattern fill)
  • Ability to display legends column-wise or row-wise when appropriate to the chart type
  • Ability to Modifying legend font size and style
  • Choice for using a transparent or colored background for the legend
  • Ability to edit legend entries annotation or reordering the entries
  • Tools for customizing binned or continuous color scale legends
Customizing Chart Axis Attributes

Axis customizing controls vary contextually depending on the graph category you are are customizing; th Axis panel provides controls for:

  • Choice of linear or logarithmic scale, forward or reverse (when applicable)
  • Using title proxy names
  • Modifying the axis line thickness, color, length and type of major and minor grids
  • Modifying the axis range and steps (when applicable)
  • Using different label display format settings (fixed or scientific format, decimal places, use of leading zero, use of a prefix or suffix, etc.)
  • Changing axis text properties and position of labels
  • Customizing axis attributes of plot types that do not share the common axis properties of 2D and 3-D charts (e.g., spider, rose, stereographic, polar, mosaic, dendrograms, etc.)
Displaying Object and Value Labels on Charts

This feature allow:

  • Optional display of object or value labels on charts ((when applicable)
  • Displaying a 3rd dimension on an XY chart, a 4th dimension on a ternary, bubble, or 3D scatter chart, using Value labels
  • Customizing labels using the Label Stylizer panel controls
More Information
Label Display Examples

Tutorial-Style eBooks

Summary of Aabel NG (NG2, v5) eBooks

Aabel NG is distributed with three high-quality PDF eBooks, which collectively include 1800 pages, and over 1100 illustrations. The eBooks provide flexible navigation controls, complete hot linked cross-referencing throughout each volume, step-by-step instructions for using the diverse features and capabilities of the application, and can produce high quality print output.

  • Aabel NG (NG2, v.5): eBook Volume I (885 pages; 518 illustrations):
    • Chapter 1. Getting Started
    • Chapter 2. Data Pipeline Design of Aabel NG
    • Chapter 3. Data Importers and the Importer Document
    • Chapter 4. Worksheet Features and Utilities
    • Chapter 5. Graphic Viewer Features, Panels and Controls
    • Chapter 6. Exporting, Copying, and Importing Graphics
    • Chapter 7. Data Visualization and Charting*
    • Chapter 8. Map Projection Utilities and Thematic Maps
    • Chapter 9. Graphic Organizer
    • Chapter 10. Curve Fitting
    • Chapter 11. Error Bars
    • Chapter 12. Chart Customizing Features
    • Chapter 13. Color Management
    • Chapter 14. Objects and Attributes
    • Chapter 15. Multi-Dimensional Data Filtering
    • Chapter 16. Data Exploration Tools
    • * This chapter covers a wide range of general-purpose and a number of specialized charts.

  • Aabel NG (NG2, v.5): eBook Volume II (885 pages; 585 illustrations):
    • Chapter 1. The Stats Analyzer General Features
    • Chapter 2. Statistics and Multivariate Analysis Modules
    • Chapter 3. Univariate & Multivariate Statistical Charts**
    • ** This chapter covers a wide range of statistical charts.

  • Aabel NG (NG2, v.5): eBook Volume III (101 pages; 56 illustrations):
    • Data Processing Utilities
  • Aabel NG Quick Start Guide for New Users (47 pages and 40 illustrations):
    • A quick start guide and examples for using the Stats Analyzer modules
    • A quick start guide and examples for using the Chart Designer panel and creating graphs
    • The significance of graphic viewer tools, selections modes, pages, and active chart pane