BlueSky Statistics (an R menu) prices


incl. 19 % VAT

BlueSky Statistics

- Provides a familiar powerful user interface available in mainstream statistical applications like SPSS, SAS etc.

- Unlocks the power of R for the analyst community by providing a rich GUI and output for several popular statistics, data mining, data manipulation and graphics commands, all out of the box...

- Provide a rich development framework for developing and deploying new statistical modules, applications or functions with rich graphical user interfaces and output, all through intuitive drag and drop user interfaces (No programming required).


BlueSky Statistics can help you

  • Migrate from expensive propriety statistical applications to R.
  • Ease the R learning curve.
  • Use the cutting edge analytics available in R without having to learn programming.
  • Get results in true word processing tables automatically.
  • Quickly add your own menus and dialog boxes to any R functions.


For sophisticated users, BlueSky Statistics provides a rich application development framework that can be used to design new modules or new statistical functions with intuitive drag and drop interfaces. In a couple of clicks these modules can be installed in the BlueSky Statistics application or distributed to a colleague empowering both the author and the consumer.

Our goal is to create a marketplace where users can share their analytical functions and modules efficiently.

BlueSky Application
  • Open, browse, edit multiple datasets, create new datasets, add/remove variables, add/remove factor levels, recode, bin.... ALL via the intuitive graphical user interface.
  • Access popular statistics, machine learning, data mining, data manipulation, and exploratory data analysis functions.
  • Access the output of the analysis in a rich graphical user interface that supports interactive tables, copy and paste into Office applications as true tables, and export to popular formats like HTML, PDF.
  • Run R programs directly and access its output.

BlueSky R Command Editor

Users of the BlueSky Statistics application are not constrained to using the graphical user interface. The syntax editor allows users to:
  • Type in and execute R syntax directly.
  • Run R programs in automated or batch mode.
  • Inspect the R syntax that any of the functions available in BlueSky Statistics applications generate when executed.
  • Learn R programming by allowing you to not only type in R syntax but also inspect the R syntax generated by BlueSky Statistics's menus and dialog boxes.
  • Create, open and save R programs for reuse.

BlueSky Output Viewer

The BlueSky Output Viewer allows you to share the results of your analysis including graphs, tables with your peers, management team or customers who don't have the BlueSky Statistics application. This gives consumers of the analytics the rich interactivity available in the BlueSky Statistics application.

BlueSky Dialog Designer

The BlueSky Dialog designer is an application development framework that allows you to create statistical modules or functions with a rich graphical user interface and output for any existing R function in any package or any new R function or package you create.
The BlueSky Dialog designer allows you to create and save the user interface and output definition for the statistics module or function in a zipped file.

Minimum system requirements

Minimum functioning specifications

Hardware Requirement Applicable operating system
Disk space Minimum free disk space. 20 GB of available hard-disk space. All supported Windows operating systems
Display A monitor with 1024×768 resolution or higher All supported Windows operating systems
Media drives A DVD-ROM drive is required if you are installing from the installation disk. All supported Windows operating systems
Memory Minimum RAM 4 GB All supported Windows operating systems
Processor Intel® Pentium® or Pentium-class processor or higher (for 32-bit Windows)  x64 (AMD 64 and EM64T) processor family (for 64-bit Windows) All supported Windows operating systems

Open Source Edition (Free)

Fully featured analytical workbench that provides :

  • An intuitive graphical user interface, attractive interactive output for hundreds of frequently used exploratory analysis, data preparation, visualization, basic and advanced modeling techniques including model scoring.
  • Automatic R syntax generation for hundreds of frequently used exploratory analysis, data preparation, visualization and modeling techniques.
  • R syntax editor that allows you to write and execute R code and see richly formatted output.
  • Save and share output in PDF, HTML.
  • Technical support is available via community forums.
License : AGPL 3.0


Commercial Edition

1. BlueSky Statistics Commercial Desktop:
The BlueSky Statistics Commercial Desktop provides all the capabilities of the open source edition plus:
  • Access to priority support, 24 hr response time during business hours
  • Service Level Agreements for delivering application support and hot fixes for critical issues
  • Prioritized bug fixes and feature requests
2. BlueSky Statistics Commercial Server:
The BlueSky Statistics Commercial Desktop provides all the capabilities of the open source edition plus:
  • Support for Citrix and Terminal server
  • Access to priority support, 24 hr response time during business hours
  • Service Level Agreements for delivering application support and hot fixes for critical issues
  • Prioritized feature requests
    Open Source   Commercial Edition
Run on terminal server   X  
Install unlimited dialogs/extensions   X  
Technical support   X  
Enterprise features (Database and customization etc.)   X  


Sub Category


Open Source


Data Management

Open Dataset

IBM SPSS (*.sav)


Excel 2003


Excel 2007-2010


Comma separated (*.csv)




SAS (*.sas7bdat)




Txt (*.txt)


Load Data

From R package


Database Connectivity









Dataset Save formats

IBM SPSS (*.sav)


Excel 2007-2010


Comma separated (*.CSV)




RObj (*.RData)


Data Preparation


Fully functional data grid


For Variables





Compute, apply a function across all rows


Compute Dummy Variables


Conditional Compute


Conditional Compute, if-then


Conditional Compute, if-then-else


Concatenate multiple variabels


Convert to factors




Delete variables


Factor Levels


-- Add New Levels


-- Display Levels


-- Drop Unused Levels


-- Label NA as 'Missing'


-- Lumping into 'Other'


-- Reorder by Occurence in Dataset


-- Reorder by One Other Variable


-- Reorder Levels Manually


-- Specify levels to keep or replace by 'Other'


Missing value analysis


Rank variables










For Dataset





Merge Datasets


Re-order variables alphabetically








Stack Datasets






Descriptive Statistics


Numerical summary analysis


Factor variable analysis




Summary by variable


Summary (group by multiple variables)


Numerical statistical analysis


Dataset Comparison


Dataset Description








Survival Analysis


Kaplan-Meier Estimation, compare groups


Kaplan-Meier Estimation, one group


Distribution, Continuous

Beta Distribution

Beta Probabilities


Beta Quantiles


Plot Beta Distribution


Sample from Beta Distribution


Cauchy Distribution

Cauchy Probabilities


Cauchy Quantiles


Plot Cauchy Distribution


Sample from Cauchy Distribution


Chi-squared Distribution

Chi-squared Probabilities


Chi-squared Quantiles


Plot Chi-squared Distribution


Sample from Chi-squared Distribution


Exponential Distribution

Exponential Probabilities


Exponential Quantiles


Plot Exponential Quantiles


Sample from Exponential Distribution


F Distribution

F Probabilities


F Quantiles


Plot F Distribution


Sample from F Distribution


Gamma Distribution

Gamma Probabilities


Gamma Quantiles


Plot Gamma Distribution


Sample from Gamma Distribution


Gumbel Distribution

Gumbel Probabilities


Gumbel Quantiles


Plot Gumbel Distribution


Sample from Gumbel Distribution


Logistic Distribution

Logistic Probabilities


Logistic Quantiles


Plot Logistic Distribution


Sample from Logistic Distribution


Lognormal Distribution

Lognormal Probabilities


Lognormal Quantiles


Plot Lognormal Distribution


Sample from Lognormal Distribution


Normal Distribution

Normal Probabilities


Normal Quantiles


Plot Normal Distribution


Sample from Normal Distribution


t Distribution

t Probabilities


t Quantiles


Plot t Distribution


Sample from t Distribution


Uniform Distribution

Uniform Probabilities


Uniform Quantiles


Plot Uniform Distribution


Sample from Uniform Distribution


Weibull Distribution

Weibull Probabilities


Weibull Quantiles


Plot Weibull Distribution


Sample from Weibull Distribution

Distribution, Discrete

Binomial Distribution

Binomial Probabilities


Binomial Quantiles


Binomial Tail Probabilities


Plot Binomial Distribution


Sample from Binomial Distribution


Geometric Distribution

Geometric Probabilities


Geometric Quantiles


Geometric Tail Probabilities


Plot Geometric Distribution


Sample from Geometric Distribution


Hypergeometric Distribution

Hypergeometric Probabilities


Hypergeometric Quantiles


Hypergeometric Tail Probabilities


Plot Hypergeometric Distribution


Sample from Hypergeometric Distribution


Negative Binomial Distribution

Negative Binomial Probabilities


Negative Binomial Quantiles


Negative Binomial Tail Probabilities


Plot Negative Binomial Distribution


Sample from Negative Binomial Distribution


Poisson Distribution

Poisson Probabilities


Poisson Quantiles


Poisson Tail Probabilities


Plot Poisson Distribution


Sample from Poisson Distribution

Graphics and Visualizations


Bar charts




Bulls Eye


Contour plot


Density plots


Frequency charts






Line charts




Pie charts


Plot of means


P-P plots


Q-Q plots




Stem and leaf plot


Strip chart


Violin plot


Statistical analysis


Correlation test


Shapiro-Wilk normality test


Compare means

T-Test, Independent samples


T-Test, One samples


T-Test, Paired samples




Multi-way ANOVA


One-way ANOVA


One-way ANOVA with Blocks


One-way ANOVA with Random Blocks

Agreement analysis


Bland-Altman Plot


Cohen's Kappa


Concordance Correlation Coefficient



Concordance Correlation Coefficient, multiple raters



Diagnostic Testing


Fleiss' Kappa


Intraclass Correlation Coefficients

Factor analysis


Principal component analysis


Factor analysis


Split datasets for analysis




Remove split


Split datastes for modeling


Random split


Stratified sampling




Contrasts Display


Contrasts Set