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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
Source Code Repository :
GitHub Link

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



Category Sub Category Description Open Source Commercial
Data Management Open Dataset IBM SPSS (*.sav)


Excel 2003


Excel 2007-2010


Comma separated (*.csv)


DBF (*.DBF)


SAS (*.sas7bdat)


DAT (*.DAT)


Txt (*.txt)






Load Data From R package






Database Connectivity MSSQL


PostgreSQL


MySQL


MS-Access






Dataset Save formats IBM SPSS (*.sav)


Excel 2007-2010


Comma separated (*.CSV)


DBF (*.DBF)


RObj (*.RData)





Data Preparation
Fully functional data grid

For Variables Binning


Compute


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


Dates


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


Recode


Standardize


Transform


Weight

For Dataset Aggregate


Merge


Merge Datasets


Re-order variables alphabetically


Reshape


Sample


Sort


Stack Datasets


Subset


Transpose





Descriptive Statistics
Numerical summary analysis


Factor variable analysis


Frequencies


Summary by variable


Summary (group by multiple variables)


Numerical statistical analysis

Dataset Comparison

Dataset Description





Analysis Tables Basic

Advanced





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


Boxplots


Bulls Eye


Contour plot


Density plots


Frequency charts


Heatmap


Histogram


Line charts


Maps


Pie charts


Plot of means


P-P plots


Q-Q plots


Scatterplot


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


ANCOVA


Multi-way ANOVA


One-way ANOVA


One-way ANOVA with Blocks


One-way ANOVA with Random Blocks






Proportion test Single sample proportion test


Single sample exact binomial proportion test


Two sample proportion test






Variance Two variance F-Test






Possessive Bartlett's test


Levene's test






Non-parametric test Chi-squared test


Friedman test


Kruskal-Wallis test


Wilcoxon test, independent samples


Wilcoxon test, paired samples






Contingency tables Multiway crosstab


Two-way crosstab

Odds Ratios, M by 2 table

Relative Risks, M by 2 table





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
Split


Remove split





Split datastes for modeling
Random split


Stratified sampling





Contrasts
Contrasts Display


Contrasts Set





Linear modeling
Generalized linear models


Linear modeling


Linear regression


Linear Regression, multiple models
*


Logistic regression


Logistic Regression, conditional
*


Logistic Regression, multiple models
*


Multinomial Logit


Ordinal Regression


Quantile Regression
*


Summarizing models for each group
Model Tuning Cox Proportional Hazards Models Cox Multiple Models *
Cox Single Model
Cox With Formula





Mixed Models
Mixed Models, basic





Tree algorithms
Decision trees


Random forest


Extreme Gradient Boosting

Neural Networks Multi-Layer Perceptron


NeuralNets





Probabilistics classifiers
Naive Bayes





Clustering
Hierarchical cluster


K-Means cluster


KNN





Forecasting
Automated Arima


Exponential smoothing


Holt-Winters, seasonal


Holt-Winters, Non-seasonal


Plot time series
Reliability Analysis

. .


Cronbach's alpha


McDonald's omega





Model tuning
Bootstrap resampling


K-fold cross validation


Leave one out cross validation


Repeated K-fold cross validation





Model statistics
AIC


BIC


Bonferroni outlier test


Confidence interval


Hosmer-Lemeshow test


IRT


Likelihood ratio test


Pseudo R squared


Stepwise


Variance inflation factors





Model scoring
Pick a model


Score the selected model


Save model


Load model





Reporting
Custom tables


Export to PDF


Export to Excel


Export to HTML


Export output table to MS-Word as APA table





Market basket
Generate rules


Item frequency


Targeting items


Display rules


Plot rules





Dialog utilities
Dialog inspector


Dialog installer










* This dialog can be installed in the Open Source edition using the dialog installer. A maximum of 5 dialogs can be installed in Open Source edition.