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  • Spotfire Statistica® Descriptive Statistics


    Description of the Descriptive statistics module.

    The module will compute common descriptive statistics including median, mode, sum, count, quartiles, user-specified percentiles, average and standard deviation, quartile range, confidence limits for the mean, skewness and kurtosis (with their respective standard errors), harmonic means, geometric means, trimmed mean, Winsorized man, Grubbs test for outlier. A selection of tests is available for fitting the normal distribution to the data via the Kolmogorov-Smirnov, Lilliefors, and Shapiro-Wilks' tests.

    Various visualizations are available like box-and-whisker plots, histograms, bivariate distribution (3D or categorized) histograms, 2D and 3D scatterplots with marked subsets, normal, half-normal, detrended probability plots, Q-Q plots, P-P plots, etc.

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    By Group Analyses

    Descriptive statistics, as well as summary graphs, can be computed for data that are categorized (broken down) by one or more grouping variables. For example, with just a few mouse clicks the user can break down the data by Gender and Age and review categorized histograms, box-and-whisker plots, normal probability plots, scatterplots, etc. If more than two categorical variables are chosen, cascades of the respective graphs can be automatically produced.

    Options to categorize by continuous variables are provided, e.g., you can request that a variable be split into a requested number of intervals, or use the on-line recode facility to custom-define the way in which the variable will be recoded (categorization options of practically unlimited complexity can be specified at any point and they can reference relations involving all variables in the dataset). In addition, a specialized hierarchical breakdown procedure is provided that allows the user to categorize the data by up to six categorical variables, and compute a variety of categorized graphs, descriptive statistics, and correlation matrices for subgroups (the user can interactively request to ignore some factors in the complete breakdown table, and examine statistics for any marginal tables).

    Large analysis designs can be specified in the breakdown procedure (e.g., 100,000 groups for a single categorization variable), and results include all relevant ANOVA statistics (including the complete ANOVA table, tests of assumptions such as the Levene and Brown-Forsythe tests for homogeneity of variance, a selection of seven post-hoc tests, etc.). Extended precision calculations (the "quadruple" precision, where applicable) are used to provide accuracy.


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