Takes an array of numbers and calculates some descriptive statistics
Descriptive statistics for server-side JavaScript
Atoll is a small descriptive statistics library
Descriptive statistics for NodeJS
🔬 Descriptive statistics for RxJS
A bunch of descriptive statistics (and related) functions
MCP server: descriptive statistics over a numeric array (mean, median, stddev, percentiles).
Generate descriptive statistics.
Online descriptive statistics algorithms.
Descriptive statistics
Get descriptive statistics of OSM QA tilesets
Simple Statistics
Calculator module for capsuleer — evaluate math expressions, round numbers, and compute descriptive statistics
vfile utility to count messages per category: failures, warnings, etc
Angular CLI builder for ESLint
Statistical utilities for Chartts. Descriptive statistics, correlation, outlier detection, and more.
Gathers usage statistics for components used during application development
Statistical routines and probability distributions.
MCP server for Chrome DevTools
vaadin-input-container
Vaadin accessibility helpers, mixins and controllers
Vaadin component base mixins
Vaadin field base mixins
A parser for the TypeScript doc comment syntax
Statistics calculations and (engineering) probability distributions
Utility-first statistics scaffolding for RustUse
Adds descriptive statistics methods to Enumerable module for use on collections or Numeric data
Descriptive Statistics Calculator
This is a simple, easy-to-use, lightweight gem for calculating everyday descriptive statistics values.
Fast computation of descriptive statistics in ruby using native code and SIMD
Calculates descriptive statistics from streams with minimal overhead
This class uses Kalman Filter updating to tally sample mean and sum of squared deviations from the average, along with min, max, and sample size. Sample variance, standard deviation, and standard error are calculated on demand.
A short description of cocoapods-entitlements-statistics.
A series of useful tools that a console should probably have, if your goal is to crunch a few numbers. It includes all the packages that I use, if you have them. Also incorporates some functional style programming and stored procedures to make your console experience even more delightful.
Descriptive statistics, linear interpolation, rounding modes, and moving averages. Lightweight math toolkit with zero dependencies.
This gem aim to calculate descriptive and inferential statistics calc.
== DESCRIPTION: rutemaweb is the web frontend for rutema. It can be used as a viewer for database files created with the rutema ActiveRecord reporter. It also provides you with some basic statistics about the tests in your database in the form of diagrams of debatable aesthetics but undoubtable value! == FEATURES/PROBLEMS: == SYNOPSIS: rutemaweb [results.db] and browse to http://localhost:7000 for the glorious view == REQUIREMENTS: * patir (http://patir.rubyforge.org) * activerecord (http://ar.rubyonrails.com/) * sqlite3 (http://rubyforge.org/projects/sqlite-ruby/) * ramaze (http://www.ramaze.net/) * ruport (http://rubyreports.org/) * acts_as_reportable * erubis * gruff/RMagick (optional, but needed if you want to see the statistics graphs)
A suite for basic and advanced statistics on Ruby. Tested on CRuby 1.9.3, 2.0.0 and 2.1.1. See `.travis.yml` for more information. Include: - Descriptive statistics: frequencies, median, mean, standard error, skew, kurtosis (and many others). - Correlations: Pearson's r, Spearman's rank correlation (rho), point biserial, tau a, tau b and gamma. Tetrachoric and Polychoric correlation provides by statsample-bivariate-extension gem. - Intra-class correlation - Anova: generic and vector-based One-way ANOVA and Two-way ANOVA, with contrasts for One-way ANOVA. - Tests: F, T, Levene, U-Mannwhitney. - Regression: Simple, Multiple (OLS), Probit and Logit - Factorial Analysis: Extraction (PCA and Principal Axis), Rotation (Varimax, Equimax, Quartimax) and Parallel Analysis and Velicer's MAP test, for estimation of number of factors. - Reliability analysis for simple scale and a DSL to easily analyze multiple scales using factor analysis and correlations, if you want it. - Dominance Analysis, with multivariate dependent and bootstrap (Azen & Budescu) - Sample calculation related formulas - Structural Equation Modeling (SEM), using R libraries +sem+ and +OpenMx+ - Creates reports on text, html and rtf, using ReportBuilder gem - Graphics: Histogram, Boxplot and Scatterplot.
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