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The Desktop
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Analyses
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Analyses

  1. Exploratory and Descriptive Data Visualization and Analysis

    • Dynamic Exploratory Graphics include Spinplots, Scatterplots, Scatterplot Matrices, Histograms, Boxplots, Parallel Coordinate Plots, Mosaic Plots, Quantile Plots, Normal Probability Plots, Quantile-Quantile Plots, Diamond Plots, Dotplots, Biplots, and Guided Tour Plots.

    • Plots support brushing and labeling, and are dynamically linked.

    • Smoothers and Contours can be added to several plots.

    • Descriptive Statistics including Means, Standard Deviations, Variances, Ranges, Quartiles, Medians, Correlations, Covariances, Distances, Frequency Tables

    • SpreadPlots (groups of dynamically interacting plot-windows) have been specially designed for several different kinds of data.
       

  2. Univariate Analysis

    • Univariate Tests including T- and Z-tests (confidence intervals) for single sample, paired samples and two independent samples data, with Wilcoxon Signed-Rank and Mann-Whitney tests in appropriate situations.

    • ANOVA - Univariate Analysis of Variance for balanced and unbalanced, one or multi-way data (data must be complete). Model may or may not include two-way (but not higher-way) interactions.

    • Multiple Regression - Univariate regression includes simple, multiple, robust, and monotonic regression.

    • SpreadPlots have been specially designed for each analysis.

     

  3. Multivariate Analysis

  4. Multiple Regression - Multivariate Multiple Regression Analysis. The spreadplot consists of a biplot, spinplot, histogram and scatterplot-matrix.

    Principal Component Analysis of correlations or covariances. The model visualization is a spreadplot composed of a biplot, spin-plot, scree-plot and scatterplot-matrix.

    Multidimensional Scaling of one or more symmetric or asymmetric matrices. The model visualization is a spreadplot composed of a scatterplot, spin-plot, scree-plot and scatterplot-matrix. The spreadplot supports graphical re-estimation of model parameters.

    Correspondence Analysis of two-way contingency tables. The model visualization is a spreadplot composed of a biplot, spinplot, residuals plot and scree-plot. The spreadplot supports graphical re-estimation of model parameters.