Application for statistics, data science, Six Sigma, Quality, DoE, and more
Leading R GUI used by hundreds of thousands of users across 135 countries. Built for data scientists, quality control, engineers, process improvement (Six Sigma) professionals, biostatisticians, statisticians, and business analysts.
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Why thousands of organizations switched to BlueSky Statistics
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Comprehensive
GUI for 400+ statistics, graphics, machine learning, modeling, quality control, reliability engineering…
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Advanced
Powered by R and Python, cutting-edge analysis, automation with scripting, reproducibility...
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Collaborate
Save analysis to MS Office, R Markdown, HTML, LaTeX, save/load projects...
Extensible
Marketplace for extensions, development framework for building new GUIs…
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Intuitive App
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Drive Innovation
Propel yourself with cutting-edge analytics in R and Python
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Boost Productivity
Consolidate point solutions, share/reproduce/reuse, no coding needed
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Save Costs
Transition from expensive proprietary software to open-source R
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Why should you switch to BlueSky Statistics from other proprietary statistics software
Trusted by thousands of organizations around the world
R GUI
Rated as the Best R GUI
Global
Used in 135+ Countries
Empowering
Used by 4000+ Organizations
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What our customers say
"BlueSky Statistics is a very welcome software option for Six Sigma alternative to Minitab. We've confirmed that BlueSky Statistics is suitable for process improvement work typically done by Lean Six Sigma Belts, including advanced work by Master Black Belts. It has everything from Hypothesis Tests to Measurement System Analysis to Process Behavior Charting and an array of DOE design generators."
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Stephen Czupryna,
Master Black Belt
Pyzdek Six Sigma Training Institute, USA
Featured Videos
This video covers basic operations such as Opening a dataset, Performing analysis, Reviewing the result, and Inspecting the R code used to perform the analysis.
This video introduces the BlueSky Statistics user interface (GUI), such as Opening datasets, Saving output, Inspecting the R code used to perform the analysis, the R Editor, and Reproducibility of the analysis.
This video focuses on the capabilities of the Data grid and the variable grid, such as entering data, adding/deleting data, creating/deleting a column (variable), and transforming variable types.
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