Using R for Statistical Training: An Application to Six Sigma Methodology for Process Improvement.

Using R for Statistical Training: An Application to Six Sigma Methodology for Process Improvement.
Using R for Statistical Training 17/04/2012 EL Cano, Using R for Statistical Training JM Moguerza, A Redchuk An Application to Six Sigma Methodology Statistical Training for Process Improvement. The Problem Approaches The R Choice The R framework Sweave Emilio L. Cano, Andr´s Redchuk and Javier e Application M. Moguerza Six Sigma Examples Environments Departamento de Estad´ıstica e Investigaciń Operativa o Universidad Rey Juan Carlos (Madrid) XXXIII Congreso Nacional de Estad´ ıstica e Investigaciń Operativa o SEIO 2012 1/28
Using R for Statistical Training Contenido 17/04/2012 EL Cano, JM Moguerza, A Redchuk 1 Statistical Training Statistical Training The Problem The Problem Approaches Approaches The R Choice The R framework Sweave Application Six Sigma Examples Environments SEIO 2012 2/28
Using R for Statistical Training Contenido 17/04/2012 EL Cano, JM Moguerza, A Redchuk 1 Statistical Training Statistical Training The Problem The Problem Approaches Approaches The R Choice The R framework Sweave 2 The R Choice Application Six Sigma The R framework Examples Environments Sweave SEIO 2012 2/28
Using R for Statistical Training Contenido 17/04/2012 EL Cano, JM Moguerza, A Redchuk 1 Statistical Training Statistical Training The Problem The Problem Approaches Approaches The R Choice The R framework Sweave 2 The R Choice Application Six Sigma The R framework Examples Environments Sweave 3 Application Six Sigma Examples Environments SEIO 2012 2/28
Using R for Statistical Training The Problem 17/04/2012 Elements of Statistical Training EL Cano, JM Moguerza, A Redchuk Statistical Training The Problem Approaches The R Choice The R framework Sweave Application Six Sigma Examples Environments SEIO 2012 4/28
Using R for Statistical Training Copy-paste Approach 17/04/2012 Approaches EL Cano, JM Moguerza, A Redchuk Statistical Training The Problem Approaches The R Choice The R framework Inconsistencies Sweave Application Errors Six Sigma Examples Environments Out-of-date non-reproducible Painful changes SEIO 2012 5/28
Using R for Statistical Training Reproducible Research Approach 17/04/2012 Approaches EL Cano, JM Moguerza, A Redchuk Statistical Training Reproducible Research The Problem Approaches The goal of reproducible research is to tie The R Choice The R framework specific instructions to data analysis and Sweave Application experimental data so that scholarship can be Six Sigma Examples recreated, better understood and verified Environments Literate Programming Literate programming is a methodology that combines a programming language with a documentation language SEIO 2012 6/28
Using R for Statistical Training Reproducible Research 17/04/2012 Workflow EL Cano, JM Moguerza, A Redchuk Statistical Training The Problem Approaches The R Choice The R framework Sweave Application Six Sigma Examples Environments SEIO 2012 7/28
Using R for Statistical Training The R System 17/04/2012 Choosing R EL Cano, JM Moguerza, A Redchuk Statistical Training What is R? The Problem Approaches R is a language and environment for statistical The R Choice The R framework computing and graphics. Sweave Application Six Sigma Examples Open Source Environments Platform independent Huge community Extensible 3 730 available http://www.r-project.org packages SEIO 2012 9/28
Using R for A LTEX, Beamer, PDF Statistical Training 17/04/2012 Choosing R EL Cano, JM Moguerza, A Redchuk A LTEX Statistical Training The Problem Approaches LaTeX is a high-quality typesetting system; it The R Choice The R framework includes features designed for the production Sweave of technical and scientific documentation Application Six Sigma Examples Environments Beamer Beamer is a LaTeX class for creating presentations that are held using a projector, but it can also be used to create transparency slides LTEXFiles can easily be converted to PDF. A SEIO 2012 10/28
Using R for Statistical Training Sweave Documents 17/04/2012 An Efficient Framework EL Cano, JM Moguerza, A Redchuk Statistical Training The Problem Approaches The R Choice Sweave The R framework Sweave A Sweave document is a plain-text file which Application merges LTEX code and R code. The R A Six Sigma Examples Environments function Sweave() converts the Sweave document (*.Rnw) into a LTEXfile (*.tex). A The code chunks are executed and the results embedded into the LTEX file. A SEIO 2012 11/28
Using R for Statistical Training Methodology at a Glance 17/04/2012 Six Sigma EL Cano, JM Moguerza, A Redchuk Statistical Training The Problem The Essense Approaches The application of the Scientific Method to The R Choice The R framework Sweave process improvement, using an easy language. Application Six Sigma Examples DMAIC Cycle Environments Roles Define Champion Measure Master Black Belt Analyze Black Belt Improve Green Belt Control SEIO 2012 13/28
Using R for Statistical Training SixSigma Package 17/04/2012 Six Sigma EL Cano, JM Moguerza, Six Sigma with R | Paper Helicopter template Using packages max A Redchuk (9.5cm) std (8cm) Statistical Training The Problem min (6.5cm) Manuals Approaches Data sets ← wings length → The R Choice The R framework Sweave Templates cut Application Learn-by-Code ? pe Six Sigma fold ↑ fold ↓ ta Examples Environments cut Six Sigma Process Map operators INPUTS cut cut tools X raw material facilities ← body length → INSPECTION ASSEMBLY TEST LABELING sheets sheets helicopter helicopter ... INPUTS INPUTS INPUTS INPUTS tape? tape? Param.(x): width NC Param.(x): operator C Param.(x): operator C Param.(x): operator C operator C cut P throw P label P Measure pattern P fix P discard P Featur.(y): label discard P rotor.width C environment N Featur.(y): ok rotor.length C Featur.(y): time paperclip C tape C min Featur.(y): weight (6.5cm) LEGEND std helicopter OUTPUTS fold ↓ ↓ fold ↑ ↑ (C)ontrollable (8cm) (Cr)itical (N)oise Y (P)rocedure clip? max Paper Helicopter Project max min ← body width → min max (9.5cm) SEIO 2012 (6cm) (4cm) (4cm) (6cm) 14/28
Using R for Statistical Training Book 17/04/2012 Six Sigma EL Cano, JM Moguerza, A Redchuk Six Sigma with R Statistical Training The Problem A live example: The entire book has been Approaches The R Choice produced using Sweave. The R framework Sweave Application The roadmap: The Six Sigma Examples Environments DMAIC Cycle The case study: paper helicopter SixSigma package: data sets, functions Easy explanations, further readings SEIO 2012 15/28
Using R for Statistical Training Sweave Example I 17/04/2012 Six Sigma Application EL Cano, JM Moguerza, A Redchuk documentclass [ a4paper ]{ article } Statistical Training usepackage { Sweave } The Problem title { Design of Experiments } Approaches author { EL Cano and JM Moguerza and A Rechuk } The R Choice begin { document } The R framework maketitle Sweave section { Introduction } Application Design of experiments is the most important took in the I Six Sigma DMAIC cycle ldots . Examples < < > >= Environments library ( SixSigma ) doe . model1 <- lm ( score ~ flour + salt + bakPow + flour * salt + flour * bakPow + salt * bakPow + flour * salt * bakPow , data = ss . data . doe1 ) summary ( doe . model1 ) @ This is the general model : begin { equation } label { eq : doe : model } SEIO 2012 16/28
Using R for Statistical Training Sweave Example II 17/04/2012 Six Sigma Application EL Cano, JM Moguerza, A Redchuk Statistical Training The Problem y_ { ijkl }= mu + alpha_i + beta_j + gamma_k +( alpha beta ) _ { ij } Approaches ( alpha gamma ) _ { ik }+( beta gamma ) _ { kl }+( alpha beta gamma The R Choice varepsilon_ { ijkl } , The R framework end { equation } Sweave And here we have a plot of effects : Application Six Sigma << maineff , echo = FALSE , fig = TRUE > >= Examples plot ( c ( -1 , 1) , ylim = range ( ss . data . doe1$score ) , Environments coef ( doe . model1 )[1] + c ( -1 , 1) * coef ( doe type =" b " , pch =16) abline ( h = coef ( doe . model1 )[1]) @ % input { section2 } end { document } SEIO 2012 17/28
Estimate Std. Error t value Pr(>|t|) (Intercept) 5.5150 0.3434 16.061 2.27e-07 *** flour+ 1.8350 0.4856 3.779 0.005398 ** salt+ -0.8350 0.4856 -1.719 0.123843 bakPow+ -2.9900 0.4856 -6.157 0.000272 *** flour+:salt+ 0.1700 0.6868 0.248 0.810725 flour+:bakPow+ 0.8000 0.6868 1.165 0.277620 salt+:bakPow+ 1.1800 0.6868 1.718 0.124081 flour+:salt+:bakPow+ 0.5350 0.9712 0.551 0.596779 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 0.4856 on 8 degrees of freedom Multiple R-squared: 0.9565, Adjusted R-squared: 0.9185 F-statistic: 25.15 on 7 and 8 DF, p-value: 7.666e-05 This is the general model: yijkl = µ + αi + βj + γk + (αβ)ij + (αγ)ik + (βγ)kl + (αβγ)ijk + εijkl , (1) 1
2
Using R for Statistical Training Project Example 17/04/2012 Divide and Conquer! EL Cano, JM Moguerza, A Redchuk Strategies Statistical Training The Problem Approaches Partial Sweave files can be compiled to get The R Choice partial LTEX files. R scripts can Sweave .Rnw A The R framework Sweave files and “source” .R files. The final document Application Six Sigma is obtained by compiling the “master” Examples Environments LTEX file. A > source("code/myoptions.R") > source("code/myfunctions.R") > source("code/mydata.R") > Sweave("rnw/theorem01.Rnw") > Sweave("rnw/lesson01.Rnw") > Sweave("rnw/exercises01.Rnw") > ... > texi2pdf("master.tex") SEIO 2012 20/28
Using R for Statistical Training Some useful extensions 17/04/2012 Packages EL Cano, JM Moguerza, A Redchuk knitr, pgfSweave: enhanced options for Statistical Training The Problem Sweave Approaches The R Choice RGIFT: Automatic generation of The R framework Sweave questionnaires for Moodle Application Six Sigma exams: Automatic generation of printable Examples Environments exams odfWeave: Open Document format documents generation More in the “Reproducible Research” Task View at CRAN. http://cran.r-project.org/web/views/ ReproducibleResearch.html SEIO 2012 21/28
Using R for Statistical Training R GUI 17/04/2012 Integrated Environments EL Cano, JM Moguerza, A Redchuk Statistical Training The Problem Approaches The R Choice The R framework Sweave Application Six Sigma Examples Environments SEIO 2012 22/28
Using R for Statistical Training R Studio 17/04/2012 Integrated Environments EL Cano, JM Moguerza, A Redchuk Statistical Training The Problem Approaches The R Choice The R framework Sweave Application Six Sigma Examples Environments SEIO 2012 23/28
Using R for Statistical Training EMACS + ESS 17/04/2012 Integrated Environments EL Cano, JM Moguerza, A Redchuk Statistical Training The Problem Approaches The R Choice The R framework Sweave Application Six Sigma Examples Environments SEIO 2012 24/28
Using R for Statistical Training Eclipse + StatET 17/04/2012 Integrated Environments EL Cano, JM Moguerza, A Redchuk Statistical Training The Problem Approaches The R Choice The R framework Sweave Application Six Sigma Examples Environments SEIO 2012 25/28
Using R for Statistical Training Summary 17/04/2012 EL Cano, JM Moguerza, A Redchuk Statistical training entail some challenges regarding contents and materials. Statistical Training The Problem Approaches The R Choice The R framework Sweave Application Six Sigma Examples Environments SEIO 2012 26/28
Using R for Statistical Training Summary 17/04/2012 EL Cano, JM Moguerza, A Redchuk Statistical training entail some challenges regarding contents and materials. Statistical Training The Problem Approaches R is the perfect partner for statistical The R Choice The R framework training. Sweave Application Six Sigma Examples Environments SEIO 2012 26/28
Using R for Statistical Training Summary 17/04/2012 EL Cano, JM Moguerza, A Redchuk Statistical training entail some challenges regarding contents and materials. Statistical Training The Problem Approaches R is the perfect partner for statistical The R Choice The R framework training. Sweave Application Reproducible research and literate Six Sigma Examples programming enhance training materials Environments quality. SEIO 2012 26/28
Using R for Statistical Training Summary 17/04/2012 EL Cano, JM Moguerza, A Redchuk Statistical training entail some challenges regarding contents and materials. Statistical Training The Problem Approaches R is the perfect partner for statistical The R Choice The R framework training. Sweave Application Reproducible research and literate Six Sigma Examples programming enhance training materials Environments quality. The use of R and LTEX through Sweave, A comprise a complete framework for statistical documentation generation. SEIO 2012 26/28
Using R for Statistical Training Summary 17/04/2012 EL Cano, JM Moguerza, A Redchuk Statistical training entail some challenges regarding contents and materials. Statistical Training The Problem Approaches R is the perfect partner for statistical The R Choice The R framework training. Sweave Application Reproducible research and literate Six Sigma Examples programming enhance training materials Environments quality. The use of R and LTEX through Sweave, A comprise a complete framework for statistical documentation generation. Extensions and integrated environments make easy exploiting the R capabilities. SEIO 2012 26/28
Using R for Statistical Training Acknowledgements 17/04/2012 EL Cano, JM Moguerza, A Redchuk Statistical Training The Problem Approaches R Core Team and R enthusiasts in general. The R Choice Springer The R framework Sweave Application This work has been partially funded by the projects: Six Sigma AGORANET project (IPT-430000-2010-32) Examples VRTUOSI www.vrtuosi.org: 502869-LLP-1-2009-ES-ERASMUS-EVC) Environments HAUS: IPT-2011-1049-430000 EDUCALAB: IPT-2011-1071-430000 DEMOCRACY4ALL: IPT-2011-0869-430000 CORPORATE COMMUNITY: IPT-2011-0871-430000 SEIO 2012 27/28
Using R for Statistical Training Discussion 17/04/2012 EL Cano, JM Moguerza, A Redchuk Statistical Training The Problem Approaches The R Choice The R framework Sweave Thanks for your Application Six Sigma Examples Environments attention ! SEIO 2012 28/28

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