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BlueSky Statistics Modules
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 BlueSky Application
- Open,
browse, edit multiple datasets, create new datasets, add/remove
variables, add/remove factor levels, recode.... 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.
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BlueSky R Editor
Users of the BlueSky Statistics application are not constrained to using the graphical user interface. The R editor allows users to:
- Type in and execute R code directly.
- Run R programs in automated or batch mode.
- Inspect the R code 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 code but also inspect the R code generated by BlueSky Statistics's menus and dialog boxes.
- Create, open and save R programs for reuse.
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BlueSky Output
The BlueSky Output 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.
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BlueSky Six Sigma
The functionality has been designed around the DMAIC methodology of Six Sigma, which is a data-driven quality strategy used to improve processes. DMAIC implies five quality improvement steps - Define, Measure, Analyze, Improve and Control. The comprehensive functionality includes
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Pareto charts, fishbone cause and effect diagrams, process capability analysis, seven types of Shewhart control charts (XBar-R, XBar-S, I-MR, I-MR Between/Within, p, np, u, c-charts) with customizable settings for testing eight special causes, the ability to label process stages/phases, T -squared/ MPCC charts, EWMA charts, and CUSUM charts, gage R&R analysis (see more details
10.1.2 Release notes
and
10.2.0 Release notes
)
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Any number of additional sigma/limit lines can be added to any of the Shewhart charts to help identify early shifts and drifts in the process data
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BlueSky DoE (Design of Experiments)
DoE is a branch of applied statistics that deals with planning, conducting, analyzing, and interpreting controlled tests to evaluate the factors (i.e., input variables) that control the value of a parameter or group of parameters (i.e., response variables). The experiments allow the designers to study/analyze the effect of each factor on the response variable and the effects of interactions between factors on the response variable. DoE is very useful in many different fields, including manufacturing, engineering/R&D, agriculture, marketing, and consumer goods, to Increase product quality, increase yield, reduce costs, or identify the desired mix of new product features/attributes. The comprehensive functionality includes
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Creating or uploading factor details (factors and levels), creating several different types of design, inspecting a design, plotting a design, exporting a design, importing design responses, and modifying a design(see more details
10.1.2 Release notes
)
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Analyzing design responses with various statistical models such as Linear Model and Response Surface Model. In addition, responses can be analyzed with Main Effects and Interaction Effects plot, Half Normal plot for 2-level to plot Daniel effects normal (or Half)
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