Six Sigma with R

1. Six Sigma With R (Springer, 2012) November, 2012 Emilio L. Cano Javier M. Moguerza Andr´s Redchuk e Six Sigma with R Frontmatter Statistical Engineering for Process Mainmatter Improvement I Basics II Deﬁne III Measure IV Analyze V Improve VI Control Emilio L. Cano, Javier M. Moguerza VII Further and Beyond Backmatter and Andr´s Redchuk e November 20, 2012 Facultad de Estudios Estad´ ısticos Universidad Complutense de Madrid Book Presentation UCM 1/59

2. Six Sigma With R (Springer, 2012) Contenido November, 2012 Emilio L. Cano Javier M. Moguerza Andr´s Redchuk e 1 Frontmatter Frontmatter Mainmatter 2 Mainmatter I Basics II Deﬁne I Basics III Measure IV Analyze V Improve II Deﬁne VI Control VII Further and Beyond III Measure Backmatter IV Analyze V Improve VI Control VII Further and Beyond 3 Backmatter Book Presentation UCM 2/59

3. Six Sigma With R (Springer, 2012) Contents November, 2012 Emilio L. Cano Javier M. Moguerza Andr´s Redchuk e 1 Frontmatter Frontmatter Mainmatter 2 Mainmatter I Basics II Deﬁne I Basics III Measure IV Analyze V Improve II Deﬁne VI Control VII Further and Beyond III Measure Backmatter IV Analyze V Improve VI Control VII Further and Beyond 3 Backmatter Book Presentation UCM 3/59

4. Six Sigma With R (Springer, 2012) Publisher November, 2012 Emilio L. Cano Javier M. Moguerza Andr´s Redchuk e Frontmatter Mainmatter I Basics II Deﬁne III Measure IV Analyze V Improve VI Control VII Further and Beyond Backmatter http://www.springer.com/statistics/book/978-1-4614-3651-5 Book Presentation UCM 4/59

5. Six Sigma With R (Springer, 2012) Book website November, 2012 Emilio L. Cano Javier M. Moguerza Andr´s Redchuk e Frontmatter Mainmatter I Basics II Deﬁne III Measure IV Analyze V Improve VI Control VII Further and Beyond Backmatter http://www.sixsigmawithr.com/ Book Presentation UCM 5/59

6. Six Sigma With R (Springer, 2012) R Package November, 2012 Emilio L. Cano Javier M. Moguerza Andr´s Redchuk e Frontmatter Mainmatter I Basics II Deﬁne III Measure IV Analyze V Improve VI Control VII Further and Beyond Backmatter http://cran.r-project.org/web/packages/SixSigma/index.html Book Presentation UCM 6/59

7. Six Sigma With R (Springer, 2012) Frontmatter November, 2012 Emilio L. Cano Javier M. Moguerza Andr´s Redchuk e Foreword Frontmatter Preface Mainmatter Why Six Sigma with R I Basics II Deﬁne Who is this book for III Measure Conventions IV Analyze V Improve Production VI Control VII Further and Beyond Resources Backmatter About the Authors Acknowledgements Contents List of Tables and Figures Acronyms http://link.springer.com/book/10.1007/978-1-4614-3652-2//page/1 Book Presentation UCM 7/59

9. Six Sigma With R (Springer, 2012) 1. Six Sigma in a Nutshell November, 2012 Emilio L. Cano Javier M. Moguerza Andr´s Redchuk e Frontmatter Herbert Spencer Mainmatter I Basics “Science is organised knowledge” II Deﬁne III Measure IV Analyze V Improve VI Control VII Further and Beyond Backmatter Book Presentation UCM 9/59

10. Six Sigma With R (Springer, 2012) The DMAIC Cycle November, 2012 Emilio L. Cano Javier M. Moguerza Andr´s Redchuk e Frontmatter Mainmatter I Basics II Deﬁne III Measure IV Analyze V Improve VI Control VII Further and Beyond Backmatter Book Presentation UCM 10/59

11. Six Sigma With R (Springer, 2012) Six Sigma Roles November, 2012 Emilio L. Cano Javier M. Moguerza Andr´s Redchuk e Frontmatter In Six Sigma, everyone in the organization has Mainmatter I Basics a role in the project. Six Sigma methodology II Deﬁne III Measure IV Analyze uses an intuitive categorization of these roles. V Improve VI Control VII Further and Beyond Backmatter Book Presentation UCM 11/59

12. Six Sigma With R (Springer, 2012) Six Sigma Roles November, 2012 Emilio L. Cano Javier M. Moguerza Andr´s Redchuk e Frontmatter In Six Sigma, everyone in the organization has Mainmatter I Basics a role in the project. Six Sigma methodology II Deﬁne III Measure IV Analyze uses an intuitive categorization of these roles. V Improve VI Control VII Further and Beyond Backmatter Book Presentation UCM 11/59

13. Six Sigma With R (Springer, 2012) 2. R from the Beginning November, 2012 Emilio L. Cano Javier M. Moguerza Andr´s Redchuk e Frontmatter Linus Torvalds Mainmatter I Basics “Software is like sex; it’s better when it’s free” II Deﬁne III Measure IV Analyze V Improve VI Control VII Further and Beyond Backmatter Book Presentation UCM 12/59

14. Six Sigma With R (Springer, 2012) The R Project November, 2012 Emilio L. Cano Javier M. Moguerza Andr´s Redchuk e Frontmatter Mainmatter I Basics II Deﬁne III Measure IV Analyze V Improve VI Control VII Further and Beyond Backmatter http://www.r-project.org Book Presentation UCM 13/59

15. Six Sigma With R (Springer, 2012) The R Environment November, 2012 Emilio L. Cano Javier M. Moguerza Andr´s Redchuk e Frontmatter Mainmatter I Basics II Deﬁne III Measure IV Analyze V Improve VI Control VII Further and Beyond Backmatter Book Presentation UCM 14/59

16. Six Sigma With R (Springer, 2012) 3. Process Mapping with R November, 2012 Emilio L. Cano Javier M. Moguerza Andr´s Redchuk e Frontmatter Charles Franklin Kettering Mainmatter I Basics “A problem well stated is a problem half II Deﬁne III Measure solved” IV Analyze V Improve VI Control VII Further and Beyond Backmatter Book Presentation UCM 15/59

17. Six Sigma With R (Springer, 2012) A Process Map November, 2012 Emilio L. Cano Javier M. Moguerza Andr´s Redchuk e Six Sigma Process Map Frontmatter operators INPUTS tools Mainmatter X raw material I Basics facilities II Deﬁne INSPECTION ASSEMBLY TEST LABELING III Measure sheets sheets helicopter helicopter IV Analyze ... INPUTS INPUTS INPUTS INPUTS V Improve VI Control VII Further and Beyond Param.(x): width NC Param.(x): operator C Param.(x): operator C Param.(x): operator C Backmatter 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 Featur.(y): weight LEGEND helicopter (C)ontrollable OUTPUTS (Cr)itical (N)oise Y (P)rocedure Paper Helicopter Project Book Presentation UCM 16/59

18. Six Sigma With R (Springer, 2012) 4. Loss Funtion Analysis with R November, 2012 Emilio L. Cano Javier M. Moguerza Andr´s Redchuk e Frontmatter W. Edwards Deming Mainmatter I Basics II Deﬁne Defects are not free. Somebody makes them, III Measure IV Analyze and gets paid for making them V Improve VI Control VII Further and Beyond Backmatter Book Presentation UCM 17/59

19. Six Sigma With R (Springer, 2012) A Loss Function Example November, 2012 Emilio L. Cano Javier M. Moguerza Andr´s Redchuk e > ss . lfa ( ss . data . bolts , " diameter " , 0.5 , 10 , 0.001 , lfa . sub = " 10 mm . Bolts Project " , Frontmatter lfa . size = 100000 , lfa . output = " both " ) Mainmatter I Basics II Deﬁne $ lfa . k III Measure [1] 0.002 IV Analyze V Improve VI Control $ lfa . lf VII Further and Beyond expression ( bold ( L == 0.002 %. % ( Y - 10) ^2) ) Backmatter $ lfa . MSD [1] 0.03372065 $ lfa . avLoss [1] 6.74413 e -05 $ lfa . Loss [1] 6.74413 Book Presentation UCM 18/59

20. Six Sigma With R (Springer, 2012) A Loss Function Example (cont.) November, 2012 Emilio L. Cano Javier M. Moguerza Loss Function Analysis Andr´s Redchuk e Frontmatter 5e−04 T Data Mainmatter I Basics 4e−04 CTQ: diameter II Deﬁne Y0 = 10 III Measure Cost of Poor Quality ∆ = 0.5 IV Analyze L0 = 0.001 3e−04 V Improve Size = 1e+05 VI Control VII Further and Beyond 2e−04 Backmatter Mean = 10.0308 k = 0.002 1e−04 MSD = 0.0337 LSL USL Av.Loss = 1e−04 Loss = 6.7441 0e+00 9.6 9.8 10.0 10.2 10.4 Observed Value L = 0.002 ⋅ (Y − 10) 2 10 mm. Bolts Project Book Presentation UCM 19/59

21. Six Sigma With R (Springer, 2012) 5. Measurement System Analysis November, 2012 Emilio L. Cano Javier M. Moguerza Andr´s Redchuk e Frontmatter Lord Kelvin Mainmatter “If you cannot measure it, I Basics II Deﬁne you cannot improve it.” III Measure IV Analyze V Improve VI Control VII Further and Beyond Backmatter Book Presentation UCM 20/59

22. Six Sigma With R (Springer, 2012) Repeatability & Reproducibility November, 2012 Emilio L. Cano Javier M. Moguerza Andr´s Redchuk e Frontmatter Mainmatter I Basics Repetible and Reproducible Repetible but non Reproducible Reproducible but non Repetible Non Repetible & Non Reproducible II Deﬁne q q III Measure qq q q q q q q q IV Analyze q q V Improve q qq q qq VI Control VII Further and Beyond q q q q q Backmatter Book Presentation UCM 21/59

23. Six Sigma With R (Springer, 2012) MSA with R November, 2012 Emilio L. Cano Javier M. Moguerza Andr´s Redchuk e Six Sigma Gage R&R Study Components of Variation Var by Part 1.8 Frontmatter 80 q q q q q 1.6 60 q q Percent Mainmatter 1.4 var 40 q q q q q q 1.2 I Basics 20 q q q q q 1.0 q 0 II Deﬁne G.R&R Repeat Reprod Part2Part q prot #1 prot #2 prot #3 III Measure %Contribution %Study Var IV Analyze R Chart by appraiser Var by appraiser prot #1 prot #2 prot #3 V Improve 1.8 q q q op #1 op #2 op #3 0.5 q q q q q VI Control 1.6 0.4 q q q VII Further and Beyond q 1.4 var 0.3 q var q q q q q q q q 0.2 1.2 q q q q q Backmatter 0.1 q q q 1.0 q q q q prot #1 prot #2 prot #3 prot #1 prot #2 prot #3 op #1 op #2 op #3 part x Chart by appraiser Part*appraiser Interaction prot #1 prot #2 prot #3 1.7 q op #1 op #2 op #3 1.7 q 1.6 q 1.6 q q 1.5 var 1.5 1.4 var 1.4 q 1.3 q q 1.3 q 1.2 1.2 q q q 1.1 q q 1.1 q q prot #1 prot #2 prot #3 prot #1 prot #2 prot #3 prot #1 prot #2 prot #3 op #1 op #3 part op #2 Helicopter Project Book Presentation UCM 22/59

24. Six Sigma With R (Springer, 2012) 6. Pareto Analysis with R November, 2012 Emilio L. Cano Javier M. Moguerza Andr´s Redchuk e Frontmatter Ovidio Mainmatter I Basics Causa latet: vis est notissima. [The cause is II Deﬁne III Measure hidden, but the result is known.] IV Analyze V Improve VI Control VII Further and Beyond Backmatter Book Presentation UCM 23/59

25. Six Sigma With R (Springer, 2012) Pareto Principle (80/20 rule) November, 2012 Emilio L. Cano Javier M. Moguerza Andr´s Redchuk e Frontmatter Mainmatter I Basics II Deﬁne Examples III Measure IV Analyze V Improve 20 % of customers make 80 % of incomes VI Control VII Further and Beyond 20 % of students get 80 % of good marks Backmatter 80 % of cost of quality is due to 20 % of the possible causes Book Presentation UCM 24/59

26. Six Sigma With R (Springer, 2012) Cause-and-eﬀect diagram November, 2012 Emilio L. Cano Javier M. Moguerza Andr´s Redchuk e Six Sigma Cause−and−effect Diagram Frontmatter Mainmatter I Basics Operator Environment Tools operator #1 height scissors II Deﬁne operator #2 cleaning tape III Measure operator #3 IV Analyze V Improve VI Control VII Further and Beyond Flight Time Backmatter paperclip model marks rotor.width2 calibrate thickness rotor.length Measure.Tool Raw.Material Design Paper Helicopter Project Book Presentation UCM 25/59

27. Six Sigma With R (Springer, 2012) Pareto Chart November, 2012 Emilio L. Cano Javier M. Moguerza Andr´s Redchuk e Pareto Chart for b.vector q Frontmatter q q q q Mainmatter q 80% q 60 I Basics Cumulative Percentage q II Deﬁne q III Measure IV Analyze Frequency 40 V Improve q VI Control VII Further and Beyond Backmatter 20 q 0 Delays Materials Customer Training Rework Errors Rain Wind Permissions Inadequate Temperature Book Presentation UCM 26/59

28. Six Sigma With R (Springer, 2012) 7. Process Capability Analysis November, 2012 Emilio L. Cano Javier M. Moguerza Andr´s Redchuk e Frontmatter Johann Wolfgang von Goethe Mainmatter One cannot develop taste from what is of I Basics II Deﬁne III Measure average quality but only from the very best. IV Analyze V Improve VI Control VII Further and Beyond Backmatter Book Presentation UCM 27/59

29. Six Sigma With R (Springer, 2012) Capability Analysis Output November, 2012 Emilio L. Cano Javier M. Moguerza Six Sigma Capability Analysis Study Andr´s Redchuk e Histogram & Density Density Lines Legend Frontmatter Target Density ST Theoretical Dens. ST Mainmatter Density LT Theoretical Density LT I Basics II Deﬁne III Measure LSL USL Specifications IV Analyze LSL: 740 Target: 750 V Improve USL: 760 VI Control VII Further and Beyond Backmatter Short Term Process Long Term 740 745 750 755 760 Mean: 749.7625 Mean: 753.7239 Check Normality SD: 2.1042 SD: 2.6958 n: 20 n: 40 Shapiro−Wilk Test Zs: 3.14 Zs: 2.33 q p−value: 0.07506 DPMO: 9952.5 q Short Term Indices Long Term qq Lilliefors (K−S) Test Cp: 1.5841 Pp: 1.2365 qq qqq p−value: 0.2291 CI: [1.4,1.7] CI: [1.1,1.3] qq qqq qq qq Cpk: 1.5465 Ppk: 0.7760 q q CI: [1.4,1.7] CI: [0.7,0.8] Normality accepted when p−value > 0.05 Winery Project Book Presentation UCM 28/59

30. Six Sigma With R (Springer, 2012) 8. Charts with R November, 2012 Emilio L. Cano Javier M. Moguerza Andr´s Redchuk e John Tukey Frontmatter Mainmatter “The greatest value of a picture is when it I Basics II Deﬁne forces us to notice what we never expected to III Measure IV Analyze see.” V Improve VI Control VII Further and Beyond Backmatter Book Presentation UCM 29/59

31. Six Sigma With R (Springer, 2012) Multi-vari chart November, 2012 Emilio L. Cano Multi−vari chart for Volume by color and operator Javier M. Moguerza Andr´s Redchuk e batch 1 q 2 q 3 q 4 q 1 2 3 Frontmatter 3 3 Mainmatter B C I Basics 18 II Deﬁne 17 III Measure 16 q q q q q q q q q IV Analyze 15 q q q q q q q q q q q q q q V Improve 14 VI Control 2 2 VII Further and Beyond B C q q 18 q Backmatter Volume q q 17 q q q q q q q 16 q q q q q q q q 15 q q q 14 1 1 B C q 18 q q q 17 q q q q q q 16 q q q q q q q 15 q q q q 14 q 1 2 3 Filler Book Presentation UCM 30/59

32. Six Sigma With R (Springer, 2012) 9. Statistics and Probability with R November, 2012 Emilio L. Cano Javier M. Moguerza Andr´s Redchuk e Frontmatter Mainmatter Aaron Levenstein I Basics II Deﬁne “Statistics are like bikinis. What they reveal is III Measure IV Analyze V Improve suggestive, but what they conceal is vital.” VI Control VII Further and Beyond Backmatter Book Presentation UCM 31/59

33. Six Sigma With R (Springer, 2012) Distributions November, 2012 Emilio L. Cano Hypergeometric Geometric Negative Binomial Poison Javier M. Moguerza Probability Probability Probability Probability 0.06 0.15 0.00 0.10 Andr´s Redchuk e 0.3 0.00 0.00 0.0 Frontmatter 0 1 2 3 4 0 10 30 10 20 30 40 0 5 10 20 Elements in class A Items extracted until first success Number of trials until 3 events Number of successful experiments per unit Mainmatter I Basics Exponential Lognormal Uniform Gamma Probability Density Probability Density Probability Density Probability Density II Deﬁne 0.0 0.4 0.8 0.0 0.6 1.2 0.0 0.2 0.4 III Measure 0.6 IV Analyze 0.0 V Improve 0 1 2 3 4 5 0 2 4 6 −0.5 0.5 1.5 0 2 4 6 8 VI Control Random Variable X Random Variable X>0 Random Variable X Random Variable X VII Further and Beyond Backmatter Beta Weibul t−Student Chi−squared Probability Density Probability Density Probability Density Probability Density 0.0 1.0 2.0 0.0 0.3 0.6 0.06 0.3 95% 5% 95% 5% 0.00 0.0 1.73 30.14 0.0 0.4 0.8 0 2 4 6 −4 0 2 4 10 30 50 Random Variable X Random Variable X Random Variable X Random Variable X F Probability Density 0.6 95% 5% 0.0 2.34 0 1 2 3 4 Random Variable X Book Presentation UCM 32/59

34. Six Sigma With R (Springer, 2012) 10. Statistical Inference with R November, 2012 Emilio L. Cano Javier M. Moguerza Andr´s Redchuk e George E.P. Box Frontmatter Mainmatter “All models are wrong; some models are I Basics II Deﬁne useful.” III Measure IV Analyze V Improve VI Control VII Further and Beyond Backmatter Book Presentation UCM 33/59

35. Six Sigma With R (Springer, 2012) Conﬁdence Interval Example November, 2012 Emilio L. Cano Javier M. Moguerza Andr´s Redchuk e Confidence Interval for the Mean Frontmatter Mean: 950.016 95% CI: [949.967, 950.064] Mainmatter StdDev: 0.267 P−Var: unknown I Basics n: 120 t: 1.98 II Deﬁne Missing: 0 III Measure IV Analyze V Improve VI Control Histogram & Density Plot Shapiro−Wilks 1.5 VII Further and Beyond Normality Test Backmatter 0.985 p−value: 0.19 1.0 density Normal q−q Plot 0.5 q qq q qq qq qq q qq q qq qq qq qq qq qq qq qq qq qq qq qq qq qq q q qq qq qq qq qq qq qq q 0.0 qq qq qqqq qq qq qq q qq qq qq qq q qq qq qq 949.0 949.5 950.0 950.5 q q q q Value of len q qq Book Presentation UCM 34/59

36. Six Sigma With R (Springer, 2012) 11. Design of Experiments with R November, 2012 Emilio L. Cano Javier M. Moguerza Andr´s Redchuk e Frontmatter R.A. Fisher Mainmatter “Sometimes the only thing you can I Basics II Deﬁne do with a poorly designed III Measure IV Analyze V Improve experiment is to try to ﬁnd out what VI Control VII Further and Beyond it died of” Backmatter Book Presentation UCM 35/59

37. Six Sigma With R (Springer, 2012) The Importance of Experimenting November, 2012 Emilio L. Cano Javier M. Moguerza Andr´s Redchuk e Frontmatter “An engineer who does not know Mainmatter experimental design is not an I Basics II Deﬁne III Measure engineer” IV Analyze V Improve VI Control VII Further and Beyond Backmatter Comment made by to one of the authors [of “Statistics for experimenters” by an ] executive of the Toyota Motor Company. Book Presentation UCM 36/59

38. Six Sigma With R (Springer, 2012) 12.Process Control with R November, 2012 Emilio L. Cano Javier M. Moguerza Andr´s Redchuk e Frontmatter Mainmatter Walter A. Shewhart I Basics II Deﬁne “Special causes of variation may be found and III Measure IV Analyze eliminated.” V Improve VI Control VII Further and Beyond Backmatter Book Presentation UCM 37/59

39. Six Sigma With R (Springer, 2012) Control Chart Plotting November, 2012 Emilio L. Cano Javier M. Moguerza Andr´s Redchuk e p Chart for stockouts 0.25 Frontmatter q q UCL Mainmatter q q 0.20 I Basics Group summary statistics II Deﬁne q III Measure 0.15 q q q q IV Analyze q V Improve q q VI Control 0.10 q q CL q VII Further and Beyond q q Backmatter q q 0.05 q q q q LCL 0.00 1 3 5 7 9 11 13 15 17 19 21 Group Number of groups = 22 Center = 0.1212294 LCL is variable Number beyond limits = 1 StdDev = 0.3263936 UCL is variable Number violating runs = 0 Book Presentation UCM 38/59

40. Six Sigma With R (Springer, 2012) 13. Other Tools and November, 2012 Emilio L. Cano Javier M. Moguerza Methodologies Andr´s Redchuk e Frontmatter Mainmatter Johann Wolfgang von Goethe I Basics II Deﬁne Instruction does much, but encouragement III Measure IV Analyze V Improve everything. VI Control VII Further and Beyond Backmatter Book Presentation UCM 39/59

41. Six Sigma With R (Springer, 2012) Other topics November, 2012 Emilio L. Cano Javier M. Moguerza Andr´s Redchuk e Frontmatter Mainmatter I Basics Failure Mode, Eﬀects, and Criticality II Deﬁne III Measure Analysis IV Analyze V Improve VI Control Design for Six Sigma VII Further and Beyond Backmatter Lean Gantt Chart Some Advanced R Topics Book Presentation UCM 40/59

43. Six Sigma With R (Springer, 2012) Case Study November, 2012 Emilio L. Cano Javier M. Moguerza Andr´s Redchuk e Frontmatter Mainmatter I Basics II Deﬁne III Measure IV Analyze V Improve VI Control VII Further and Beyond Backmatter Book Presentation UCM 42/59

44. Six Sigma With R (Springer, 2012) Helicopter Template November, 2012 Emilio L. Cano Javier M. Moguerza Andr´s Redchuk e Frontmatter Mainmatter I Basics II Deﬁne III Measure IV Analyze V Improve VI Control VII Further and Beyond Backmatter > ss . heli () null device 1 > # vignette (" H e l i c o p t e r I n s t r u c t i o n s ") to get instructions Book Presentation UCM 43/59

45. Six Sigma with R | Paper Helicopter template max (9.5cm) std (8cm) min (6.5cm) ← wings length → cut ? pe fold ↑ fold ↓ ta cut cut cut ← body length → tape? tape? min (6.5cm) std fold ↓ ↓ fold ↑ ↑ (8cm) clip? max max min ← body width → min max (9.5cm) (6cm) (4cm) (4cm) (6cm)

46. Six Sigma With R (Springer, 2012) Enjoy the Case Study! November, 2012 Emilio L. Cano Javier M. Moguerza Andr´s Redchuk e Frontmatter Mainmatter I Basics II Deﬁne III Measure IV Analyze V Improve VI Control VII Further and Beyond Backmatter Book Presentation UCM 45/59

47. Six Sigma With R (Springer, 2012) Enjoy the Case Study! November, 2012 Emilio L. Cano Javier M. Moguerza Andr´s Redchuk e Frontmatter Mainmatter I Basics II Deﬁne III Measure IV Analyze V Improve VI Control VII Further and Beyond Backmatter Book Presentation UCM 45/59

48. Six Sigma With R (Springer, 2012) So what? November, 2012 Emilio L. Cano Javier M. Moguerza Andr´s Redchuk e Frontmatter Mainmatter I Basics II Deﬁne III Measure IV Analyze V Improve VI Control VII Further and Beyond Backmatter Book Presentation UCM 46/59

49. Six Sigma With R (Springer, 2012) So what? November, 2012 Emilio L. Cano Javier M. Moguerza Andr´s Redchuk e The Scientiﬁc Method Frontmatter Mainmatter I Basics II Deﬁne III Measure IV Analyze V Improve VI Control VII Further and Beyond Backmatter Book Presentation UCM 46/59

50. Six Sigma With R (Springer, 2012) The Scientiﬁc Method and Six November, 2012 Emilio L. Cano Javier M. Moguerza Sigma Andr´s Redchuk e Frontmatter Mainmatter DMAIC Cycle Scientific Method I Basics II Deﬁne Ask a question III Measure Define IV Analyze V Improve Do some background VI Control Measure research VII Further and Beyond Backmatter Construct a hypothesis Analyze Test the hypothesis with an experiment Improve Analyze the data and draw conclusions Control Communicate results Book Presentation UCM 47/59

51. Six Sigma With R (Springer, 2012) The Key to Success November, 2012 Emilio L. Cano Javier M. Moguerza “Six Sigma speaks the language of business” Andr´s Redchuk e Frontmatter ISO 13053-1:2011 Mainmatter I Basics II Define III Measure IV Analyze Six Sigma methodology is a quality paradigm V Improve VI Control that translates the involved scientific VII Further and Beyond Backmatter methodology into a simple way to apply the scientific method within every organization. Book Presentation UCM 48/59

52. Six Sigma With R (Springer, 2012) Opportunities November, 2012 Emilio L. Cano Javier M. Moguerza Andr´s Redchuk e Frontmatter For Today’s Graduate, Just One Word: Statistics Mainmatter (The New York Times, August 2009) I Basics II Deﬁne “I keep saying that the sexy job in the III Measure IV Analyze next 10 years will be statisticians” V Improve VI Control VII Further and Beyond Backmatter Data Scientist: The Sexiest Job of the 21st Century (Harvard Business Review, October 2012) . . . the “data scientist.” It’s a high-ranking professional with the training and curiosity to make discoveries in the world of big data . . . Book Presentation UCM 49/59

53. Six Sigma With R (Springer, 2012) Opportunities (cont.) November, 2012 Emilio L. Cano Gartner Sees 4.4M Big Data Jobs by 2015 Javier M. Moguerza Andr´s Redchuk e (Information Management, October 2012) Frontmatter Lack of data scientists could derail big data Mainmatter I Basics projects: IBM (CIO, October 2012) II Deﬁne III Measure IV Analyze Son las matem´ticas, est´pido (El Pa´ a u ıs, V Improve VI Control Noviembre 2012) VII Further and Beyond Backmatter La econom´ del conocimiento exige ıa una educaci´n sustentada en tres o fundamentos: un nivel avanzado en matem´tica y estad´ a ıstica, una capacidad elevada para escribir un argumento y un nivel avanzado de ingl´s e Book Presentation UCM 50/59

54. Six Sigma With R (Springer, 2012) R Final Remarks November, 2012 Emilio L. Cano Javier M. Moguerza Andr´s Redchuk e Frontmatter Mainmatter I Basics II Deﬁne III Measure IV Analyze V Improve VI Control VII Further and Beyond kdnuggets.com Backmatter (2012) link Book Presentation UCM 51/59

55. Six Sigma With R (Springer, 2012) R Final Remarks (cont.) November, 2012 Emilio L. Cano Javier M. Moguerza Community Andr´s Redchuk e 4131 packages at CRAN (18/11/2012) Frontmatter Mainmatter Task views I Basics II Deﬁne III Measure Manuals IV Analyze V Improve Publications VI Control VII Further and Beyond Backmatter http: //cran.r-project.org/web/packages/ Book Presentation UCM 52/59

56. Six Sigma With R (Springer, 2012) R Final Remarks (cont.) November, 2012 Emilio L. Cano Javier M. Moguerza Andr´s Redchuk e Customization A company can develop a package that ﬁts its Frontmatter Mainmatter inner procedures and methods. I Basics II Deﬁne III Measure IV Analyze V Improve Innovation VI Control VII Further and Beyond A company can develop and deploy an Backmatter innovative method from its R&D department, or from the result of other published researches. Book Presentation UCM 53/59

57. Six Sigma With R (Springer, 2012) R Final Remarks (cont.) November, 2012 Emilio L. Cano Javier M. Moguerza Andr´s Redchuk e Frontmatter Business Mainmatter I Basics http: II Deﬁne III Measure //www.revolutionanalytics.com/ IV Analyze V Improve VI Control http://www.openanalytics.eu/ VII Further and Beyond Backmatter http://www.fellstat.com/ http://www.rstudio.com/ide/ http://www.datanalytics.com/ ... Book Presentation UCM 54/59

58. Six Sigma With R (Springer, 2012) R Final Remarks (cont.) November, 2012 Emilio L. Cano Javier M. Moguerza Andr´s Redchuk e Frontmatter Mainmatter I Basics GUI, IDE II Deﬁne III Measure RStudio IV Analyze V Improve VI Control Eclipse + StatET VII Further and Beyond Backmatter EMACS + EES Deducer ... Book Presentation UCM 55/59

59. Six Sigma With R (Springer, 2012) R Final Remarks (cont.) November, 2012 Emilio L. Cano Javier M. Moguerza Andr´s Redchuk e Frontmatter Mainmatter I Basics II Deﬁne III Measure IV Analyze V Improve VI Control VII Further and Beyond Backmatter Book Presentation UCM 56/59

60. Six Sigma With R (Springer, 2012) November, 2012 Emilio L. Cano Javier M. Moguerza Andr´s Redchuk e Frontmatter Mainmatter I Basics II Deﬁne III Measure IV Analyze V Improve VI Control VII Further and Beyond Backmatter http://r-es.org/ Book Presentation UCM 57/59

61. Six Sigma With R (Springer, 2012) November, 2012 Emilio L. Cano Javier M. Moguerza Andr´s Redchuk e Frontmatter Mainmatter I Basics II Deﬁne III Measure IV Analyze V Improve VI Control VII Further and Beyond Backmatter http://www.r-project.org/useR-2013 Book Presentation UCM 58/59

62. Six Sigma With R (Springer, 2012) Discussion November, 2012 Emilio L. Cano Javier M. Moguerza Andr´s Redchuk e Thanks ! Frontmatter Mainmatter I Basics II Deﬁne III Measure IV Analyze V Improve VI Control VII Further and Beyond Backmatter emilio.lopez@urjc.es @emilopezcano http://www.sixsigmawithr.com Book Presentation UCM 59/59

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Six Sigma with R

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