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BlueSky Statistics – A Comprehensive Quality Engineering, Process Improvement and Six Sigma Software 

  • A comprehensive  statistics, data analytics, and visualization software to support all your process and quality improvement initiatives (based on well-known DMAIC methodology)

  • Designed for Quality engineers, Reliability & Quality Assurance specialists, Process Improvement professionals, and Six Sigma practitioners of all expertise levels

  •  A point-and-click, intuitive user interface to perform data analysis without requiring any programming knowledge  

  • Based on R, a well-known and widely used statistical and data visualization software with unmatched depth and breadth of analytics

BlueSky Statistics (PRO) – Key Features for Quality/Process Improvement 

  • Load files or cut & paste data from Excel onto the BlueSky Statistics data grid, undo/redo data edits

  • Measurement System Analysis – Gage R&R, Attribute Agreement, Linear Bias, and Design Gage Study 

  • Process Capability Analysis - For normal & non-normal data

  • Statistical Process Control (SPC) Charts – xbar, R, S, p, np, c, u, I-MR (Between/Within), Mult-Vari, T-squared, EWMA, Cusum 

  • Descriptive statistics, Data prep/data cleanup, etc. 

  • Normal and non-normal Distribution Fit Analysis

  • Hypothesis Testing (T-test one-sample, two-sample, paired, proportions, ANOVA, etc.)

  • Equivalence Testing (one-sample, two-sample, paired, MET/minimal effects)

  • Regression Analysis (Linear, Non-Linear, Logistics, etc.)

  • User interface in multiple (thirteen) languages

  • Graphical Analysis (Pareto, Pie, Bar, Box, Line, Histogram, Interval, Interaction, Scatter, Scatter Matrix, Dot/Strip, Violin, Stem/Leaf, etc.)

  • Time Series/Run Chart

  • Draw additional reference/specification lines (horizontal and vertical) on graphs and plots  

  • Tolerance Intervals 

  • Survival/Reliability Analysis (parametric and non-parametric)

  • Design of Experiments (DoE) – Design and perform various experiments 

  • Project – create/save/close to save/open/validate/audit analysis work easily and share/collaborate analysis with others

  • Many more Advanced Statistics, Modeling, Machine Learning, etc.

  • Supported on both Windows and Mac

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Load data files or copy from Excel and paste onto BlueSky Data Grid 

  • Option1: Open/load any data files (Excel, CSV, other formats) from disk into the BlueSky Statistics app directly with File>Open menu

  • Option2: Copy from Excel any number of rows and columns (copy or “<ctrl> c” to copy into the clipboard) and paste into the BlueSky Statistics data grid

  • Undo/redo BlueSky Statistics app data grid edits

Gauge Repeatability & Reproducibility (Gauge R&R – Crossed & Nested)

  • Evaluate measurement system performance and identify sources of variation

  • Repeatability (variation due to measurement system precision) 

  • Reproducibility (variation due to different operators or conditions)

  • Historical process std dev to estimate Gage Evaluation values, compute %Process 

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Measurement System (MSA) - Attribute Agreement Analysis

  • Assess the agreement (i.e., Pass/Fail. Good/No-Good) or reliability of categorical measurements or observations by Operators/Raters 

  • Agreement analysis within, between, and against standards/references for Operators

  • Accuracy and Misclassification by Operators against standards/ references

Measurement System (MSA) - Gage Linearity Bias Analysis

  • Assess and quantify the systematic error or bias in the linearity of measurement systems with statistical analysis, such as linear regression

  • Linearity and Type-1 tests for one or more References in one go

  • Gage Bias, Gage capability Cg, Cgk %RE, %EV are computed and compared to the required/cut-off values specified by users on the dialog

  • Historical std dev to calculate RF (Reference Figure)

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MSA: Generate/Setup Experiment Table for a Gage Study

  • Specify the number of parts, number of operators, number of replications, randomization, sorting, etc.

  • It produces a run table for operators to schedule the experiments

SPC (Statistical Process Control)/Shewhart and Other Run Charts

  • Variable data control charts - xbar, R, S charts

  • Attribute data control charts - p, np, u, c charts

  • Individual and moving range (I-MR) charts, I-MR Between/Within charts

  • Before and After (multi-phase) chart

  • Testing for eight special causes (e.g., K points in a row, all increasing or all decreasing, etc.)

  • Ability to label process stages/phases

  • Multi-Vari charts

  • Other charts - T-squared/ MQCC, EWMA, CUSUM charts

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SPC/Control Charts – Before and After (i.e., multi-phase) Analysis 

  • Before and After (multi-phase) analysis control chart

  • Ability to label process stages/phases

  • Supports up to 10 different phases to plot side-by-side

  • I-MR chart with any number of additional reference/spec lines and optional Date x-axis instead of x-axis group numbers

Process Capability for Normal Data 

  • Computes process capability indices to assess how well the process output meets the specified requirements or the tolerance limits. 

  • Indices computed, such as Pp, Ppk, etc., for overall process capability and Cp, Cpk, etc., for potential (within) process capability

  • Option for using Unbiasing constant to estimate std dev for overall process capability indices

  • Draw any number of vertical reference/spec lines in addition to LSL, USL, and Target lines

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Process Capability for Non-normal Data 

  • Many distributions to choose from to compute the process capability indices for the non-normal data 

  • One-sided or both-sided i.e. LSL, USL, or both can be specified

  • Draw any number of vertical reference/spec lines in addition to LSL, USL, and Target lines

Survival/Reliability Analysis – Parametric and Non-Parametric

  • Non-parametric Kaplan-Meier Estimation

  • Parametric Survival (Weibull, Exponential, Log Normal, …)

  • Non-parametric Cox Regression

  • Parametric Survival Regression

  • Survival model Evaluation/Predict survival, failure, cumulative hazards

  • Overlay Kaplan-Meier curve on parametric survival/failure plots to compare

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Tolerance Interval Analysis

  • Capture a specified proportion of a population within a certain confidence level.

  • Compute the tolerance interval to find the range of values for a distribution with confidence limits calculated to a particular percentile of the distribution. 

  • Tolerance intervals provide limits where at least a certain proportion of the population (P) falls for a given confidence level (1 − α).

Graphs/Plots

  • Many Graphics/Plots – Pareto Chart, Scatter Plot, Scatter Plot Matrix, Bar Chart, Pie Chart, Histogram, Box Plot, Line Chart, Dot/Strip, Stem & Leaf, Violin, etc.

  • Interval Plot, Interaction Plot

  • Time series plot

  • Any number of reference/specification lines can be drawn on the Scatter Plot, Advanced Line Chart, Time Series Plot, Box Plot, Interval Plot, SPC charts, and Process Capability Plots

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Pareto Chart

  • Long, wide, raw data format supported to plot the commutative frequency of defects, events, etc, to identify areas of focus

  • Optional grouping variable

Scatter Plot with Smoothing Model Fit line

  • Optional grouping variables (group, row facet, column facet)

  • Many choices of smoothing fitted line model (lm, glm, cubic, quadratic, etc.)

  • Save models for each group to use later for prediction 

  • Draw any number of reference/specification lines on the plot

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Scatterplot Matrix Graphics

  • Scatterplot Matrix graphics

  • Choose any number of variables to create the matrix plot

Time Series Plot/Run Charts

  • Plot any data against a time axis

  • Flexible formatting options for both date and time label/text shown on the axis

  • Option to angle (degree) the label/text to avoid crowding of label/texts on the axis

  • Optional grouping variables to segment the plot per group

  • Draw any number of reference/specification lines on the plot

  • Plot up to milliseconds and microseconds 

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Interval Plot

  • Scatter Plot with mean and confidence interval bar 

  • An unlimited number of grouping variables for the X-axis to group a numeric variable for the Y-axis

  • Draw any number of reference/specification lines on the plot

  • Grouping color legends for easy comparison among groups

Main Effect and Interaction Plot

  • A Main Effect Plot is to examine how changes in the levels of one factor affect the response variable while ignoring the influence of other factors

  • An Interaction Plot is to examine the effect of one factor on the response variable changes depending on the level of another factor

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Box Plot

  • Box Plot with any number of reference/specification lines

  • Display numbers – 1Q, Median, and 3Q on each box

  • Optional grouping variable to plot by groups to compare

Histogram with Normal Curve Overlay

  • Histogram plot with binning and optional grouping, normal curve overlay, and counts

  • Plot bins side-by-side or stacked for different groups

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Multi-Vari Chart

  • Plot the relationship of variation of data (numerical data) against one or more factors (categorical variables)

  • Displays the mean for each factor and factor combinations

  • If more than two factor combinations are needed, an Interval Plot (unlimited grouping/factor variables) can be used

Pie Chart and Bar Chart with Counts and % 

  • The advanced Pie chart and Bar chart show % and counts on the plot

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Normal Distribution Plot 

  • Show computed probability and x values on the plot for the shaded area for x value and quantiles, respectively

  • Plot one tail (left and right), two tails, and other ranges

Model Fitting (linear, nonlinear regressions and other models)

  • Many types of model fitting (Regression, GLZM, KNN, Neural Nets, Decision Trees, SEM)

  • Regression Model - Linear, Logistic, Multinomial, Ordinal, Quantile, etc.

  • Survival/Reliability Model –  Non-parametric (Cox) and parametric (Weibull, Exp, Log Normal, Log Logistic, Gamma)

  • Nonlinear Regression – Polynomial, Nonlinear Least Square

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Regression – Model Prediction (i.e. Model Scoring)

  • Prep data to predict/score – either load data from an Excel or click the + on the data grid to create a blank data grid to type in the data (make sure to type variable names as the column names used in the model)

  • Data used for prediction must match (exact name and the case) the independent variable names used in the model 

  • Choose the correct model from the Model Evaluation > Predict > Model Scoring UI

  • Click the option if Confidence (CI) and Prediction (PI) intervals need to be computed in addition to just the prediction value

Add a Sample number to the Dataset prepping for other analysis 

  • Add a Sample number to the dataset if it is missing before running other quality/process analysis (e.g., process capability analysis, SPEC charts like xbar, R, and S charts, etc.)

  • Sample number of any sample size

  • The last data group size may not be multiple of the sample size

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Compute and Add Moving Average to the Dataset

  • Compute the Moving Average of any variable of a given grouping size 

  • Add the result back to the dataset as a new column

  • Use the Moving Average values to plot time series/run chart to observe shifts/drifts

Descriptive Statistics, Normality, and Non-normal Distribution Fit Test

  • Descriptive/Exploratory Statistics

  • Min, Max, Mean, Median, Mode, Range, Quartile, Standard Deviation, Variance, Skew, etc.

  • Normality tests (Shapiro-Wilk, Anderson-Darling, Kolmogorov-Smirnov)

  • Distribution Fit analysis and comparison for different non-normal distributions (many non-normal distributions to choose from)

  • Determine the best distribution fit based on p-values, or AIC/BIC, or both

  • Data transformation with Box-Cox, Log, and others 

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Hypothesis Tests

  • T-Test – one sample, paired sample, independent sample

  • Equivalence (and minimal Effect) Test- one sample, paired sample, independent sample

  • ANOVA – one-way, two-way, N-way

  • Proportion Tests – one sample, two sample

DoE – Design of Experiments 

  • Create or upload factor details (factors and levels)

  • Create several different types of design

  • Export design, perform experiments, import design response

  • Analyzing design responses with statistical models – Linear, Response Surface Models, etc. 

  • Analyze with Main Effects and Interaction Effects plot, Half Normal plot for 2-level to plot Daniel effects normal (or Half)

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Simplified Date/Time Conversion From Character Strings

  • Convert character date, time, or date-time strings to date variables for analysis or plotting (i.e., Time Series, Advanced Line Chart, Scatter Plot)

  • Partial character string also converted to date variables

  • Milliseconds and microseconds are supported

Rename Output Tabs  – Organize and Categorize Analysis

  • Organize analysis into multiple tabs

  • Rename output tabs to meaningful names

  • Recall dialog/analysis and continue to refine options to fine-tune the analysis

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Project – Save/Load/Share/
Collaborate/Reuse/Reproduce

  • Save analysis into one or more projects with all datasets and analysis

  • Switch between multiple projects

  • Share projects (a single .bsp file) and collaborate with colleagues 

  • Load projects (a single .bsp file), Rerun/Reproduce and validate or modify analysis performed by others

Changing the language of the UI from English (default) to another language (e.g., Spanish)

  • Launch the application for the first time – it will launch in all English

  • Thirteen languages are supported on the user interface (additional language support can be added upon request)

  • Once the new language selection has been applied, close and restart the BlueSky Statistics application to see all toolbar menus and dialog UIs in that desired language.

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Language Supported

English, Spanish, French, German, Italian, Portuguese, Romanian, Chinese (Simplified), Chinese (Traditional), Japanese, Korean, Arabic, Turkish

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Menus and dialog UIs changed to the selected language

  • After restarting the application, you will see the menus and dialog UIs in the selected language (e.g., Spanish)

  • Help (?) content on each dialog UI is also displayed in the selected language (e.g., Spanish)

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