Data analysis - Wikipedia
Data analysis is the process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making.[1] Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, and is used in different business, science, and social science domains.[2] In today's business wor
Exploratory data analysis - Wikipedia
In statistics, exploratory data analysis (EDA) is an approach of analyzing data sets to summarize their main characteristics, often using statistical graphics and other data visualization methods. A statistical model can be used or not, but primarily EDA is for seeing what the data can tell us beyond the formal modeling and thereby contrasts traditional hypothesis testing. Exploratory data analysi
Class: Statsample::Factor::PCA
Principal Component Analysis (PCA) of a covariance or correlation matrix.. NOTE: Sign of second and later eigenvalues could be different using Ruby or GSL, so values for PCs and component matrix should differ, because extendmatrix and gsl’s methods to calculate eigenvectors are different. Using R is worse, cause first eigenvector could have negative values! For Principal Axis Analysis, use Statsam
Statsample: Statistic Library for Ruby
Description Statsample is a statistical library for Ruby. Has modules for descriptive and inferencial statistics. Compatible with Ruby 1.8.7, 1.9.1, 1.9.2 and ruby-head Features: Classes for Vector, Datasets (set of Vectors) and Multisets (multiple datasets with same fields and type of vectors), and multiple methods to manipulate them. Converters to and from database (using dbi), csv (standard lib
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GitHub - clbustos/statsample: A suite for basic and advanced statistics on Ruby.
Class: Statsample::Bivariate::Pearson
statsample - Google Groups
Google Code Archive - Long-term storage for Google Code Project Hosting.
Class: Statsample::CSV
