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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

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 Server 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


Compute with Switch


Concatenate multiple variabels


Convert to Factors


Date to Character


Character to Date


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


-- Remove NAs


-- Numeric


-- Character/Factor


-- Model Imputation


-- Use A Formula


Rank variables


Recode


Standardize


Transform


Weight

For Dataset Aggregate


Expand


Merge


Merge Datasets


Re-order variables alphabetically


Reshape


-- Wider


-- Longer


Sampling


-- Sample


-- Random Split


-- Stratified Split


-- Up Sample


-- Down Sample


Sorting


-- Reorder Variables


-- Sort


Split


Stack Datasets


Subset


Transpose


-- Select Variables


-- Entire Dataset





Descriptive Statistics
Numerical summary analysis


Factor variable analysis


Frequencies


Descriptive


Summary by variable


Summary (group by multiple variables)


Numerical statistical analysis


Dataset Comparison


Dataset Description





Analysis Tables Basic


Advanced





Analysis Missing Values Row Layout


Column Layout





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


2D Contour plot


Coxcomb


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


Two Y Axis


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


ANOVA, N Way


ANOVA, 1 Way


ANOVA, 1 Way, Blocks


ANOVA, 1 Way, Random Blocks


ANOVA, 1 and 2 Way


ANOVA, Repeated Measures, Long


ANOVA, Repeated Measures, Wide


MANOVA






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, One sample


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 Fitting Cox Proportional Hazards Models Cox Multiple Models *


Cox Single Model


Cox With Formula
Model Fitting
KNN


Predict With KNN





Mixed Models
Mixed Models, basic





Tree algorithms
Decision trees


Random forest


Extreme Gradient Boosting


Optimize


Tune

Neural Networks Multi-Layer Perceptron


NeuralNets





Probabilistics classifiers
Naive Bayes





Clustering
Hierarchical cluster


K-Means cluster










Forecasting
Automated Arima


Exponential smoothing


Holt-Winters, seasonal


Holt-Winters, Non-seasonal


Plot time series, Separate or Combined


Plot time series, With Correlations
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
Add Statistics To Dataset


ANOVA & Likelihood Ratio


AIC


BIC


Bonferroni outlier test


Compare Models


Compare N Models


Confidence interval


Hosmer-Lemeshow test


IRT


Pseudo R squared


Outlier Test


Plot a Model


Stepwise


Summarize


-- Model Statistics


-- Parameter Estimates


-- Summarize A Model


-- Summarize N Model


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.