Statistics

  • Descriptive Statistics
    Creates basic descriptive statistics, such as means, medians, standard deviations, quartiles, etc. for all continuous variables; frequency tables and histograms for all categorical (class) and continuous variables. At Level of Detail = Comprehensive, Skewness, Kurtosis, Mode, etc. are also computed. When All results is requested, the program also reports normal expected frequencies, Kolmogorov-Smirnov and Lilliefors Tests for Normality, Shapiro-Wilk's W Test for continuous variables, and normal probability plots. For frequency tables and histograms you can specify the method of categorization, and/or the number of intervals to use for tabulating the continuous variables. For categorical variables with specific codes, the frequency tables and histograms will be computed using those codes.
  • Standard Multiple Regression
    Standard Multiple Regression performs standard regression analysis for the continuous dependent variable on the continuous independent variables. Both standard regression and regression through the origin (intercept=0) can be computed. Predicted and residual values can be computed as an option.
  • Main Effects ANOVA
    Main effects linear models; builds a linear model to include main-effects only for categorical predictors (use factorial ANCOVA to include continuous predictors). Both univariate (single continuous dependent variable) and multivariate (multiple continuous dependent variables) designs can be analyzed. Default results include the ANOVA (MANOVA) table and plots of means; set the Level of detail parameter to All results to request tables of means and other statistics.
  • Observed vs. Expected Chi-Square
    Observed vs. expected Chi-Square test; computes the observed vs. expected Chi-square test for one continuous dependent variable (with observed frequencies) based on the expected frequencies in one continuous predictor variable. No further parameter specifications are required.
  • Distribution Fitting
    Distribution fitting; fits various continuous and discrete distributions to variables, and computes frequency tables with expected frequencies and goodness-of-fit tests.
  • Advanced Linear and Nonlinear Models
  • Multivariate Exploratory Techniques
  • Industrial Statistics and Six Sigma
  • Variance Estimation and Precision
  • Power Analysis
  • TextMiner
    Provide powerful tools to process unstructured (textual) information, extract meaningful numeric indices from the text, and, thus, make the information contained in the text accessible to the various data mining (statistical and machine learning) algorithms available in the STATISTICA system. Information can be extracted to derive summaries for the words contained in the documents or to compute summaries for the documents based on the words contained in them. Hence, you can analyze words, clusters of words used in documents, etc., or you could analyze documents and determine similarities between them or how they are related to other variables of interest in the data mining project.
  • Data-Mining