SlideShare une entreprise Scribd logo
1  sur  12
Télécharger pour lire hors ligne
Graphical Tools SigmaXL® Version 6.1
Basic and Advanced (Multiple) Pareto Charts

EZ-Pivot/Pivot Charts

Multiple Boxplots and Dotplots

Multiple Normal Probability Plots (with
95% confidence intervals to ease
interpretation of normality/non-normality)

Run Charts (with Nonparametric Runs Test
allowing you to test for Clustering, Mixtures,
Lack of Randomness, Trends and Oscillation.)

Multi-Vari Charts
Basic Histogram

Multiple Histograms and Descriptive Statistics
(includes Confidence Interval for Mean and StDev.,
as well as Anderson-Darling Normality Test)

Multiple Histograms and Process Capability
(Pp, Ppk, Cpm, ppm, %)

Scatter Plots (with linear regression and
optional 95% confidence intervals and
prediction intervals)

Scatter Plot Matrix
Graphical Tools:
Multiple Pareto Charts

2

Customer Type - Customer Type: # 1 - Size of Customer:
Large

6
4
2

Ordertakestoo-long

Notavailable

Wrongcolor

Difficultto-order

Returncalls

0

Customer Type - Customer Type: # 1 - Size of Customer:
Small

Ordertakestoo-long

10
8
6
4
2
0

Ordertakestoo-long

8

12

Notavailable

10

100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%

14

Count

12

Count

Customer Type - Customer Type: # 2 - Size of Customer:
Large

100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%

14

Notavailable

0

Ordertakestoo-long

Notavailable

Wrongcolor

Difficultto-order

Returncalls

0

4

Wrongcolor

2

6

Wrongcolor

4

8

Difficultto-order

6

10

Difficultto-order

8

12

Returncalls

Count

10

Returncalls

12

100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%

14

Count

100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%

14

Customer Type - Customer Type: # 2 - Size of Customer:
Small

Back to
Index
Graphical Tools: EZ-Pivot/Pivot
Charts – The power of Excel’s
Pivot Table and Charts are now
easy to use!
Size of Customer (All)

70

Count of Major-Complaint

60

50

40

Customer Type
3
2
1

30

20

10

0
Difficult-to-order

Not-available

Order-takes-too-long

Return-calls

Wrong-color

Major-Complaint

Back to
Index
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
9
109
0

Run Chart - Avg days Order to delivery time

Graphical Tools:
Run Charts with
Nonparametric Runs Test

67.40

62.40

57.40

52.40
Median: 49.00

47.40

42.40

37.40

32.40

Back to
Index
Basic Histogram
Count = 100
Mean = 3.530
Stdev = 0.904031
Minimum = 1

45

25th Percentile (Q1) = 3
50th Percentile (Median) = 4

40

95% CI Mean = 3.351 to 3.709
95% CI Sigma = 0.793746 to
1.050191

35

Anderson-Darling Normality Test:
A-Squared = 5.417

25
20
15
10
5

6.00

Loyalty - Likely to Recommend

5.00

4.00

3.00

2.00

0
1.00

Frequency

30

Back to
Index
Graphical Tools:
Multiple Histograms &
Descriptive Statistics
12

Overall Satisfaction - Customer Type: 1
10

Count = 31
Mean = 3.3935
Stdev = 0.824680
Range = 3.1

8
6

Minimum = 1.7200
25th Percentile (Q1) = 2.8100
50th Percentile (Median) = 3.5600
75th Percentile (Q3) = 4.0200
Maximum = 4.8

4
2

4.98

4.71

4.44

4.17

3.90

3.62

3.35

3.08

2.81

2.54

2.26

1.99

1.72

0

Overall Satisfaction - Customer Type: 1

95% CI Mean = 3.09 to 3.7
95% CI Sigma = 0.659012 to 1.102328
Anderson-Darling Normality Test:
A-Squared = 0.312776; P-value = 0.5306

12

Overall Satisfaction - Customer Type: 2

10

Count = 42
Mean = 4.2052
Stdev = 0.621200
Range = 2.6

8
6

Minimum = 2.4200
25th Percentile (Q1) = 3.8275
50th Percentile (Median) = 4.3400
75th Percentile (Q3) = 4.7250
Maximum = 4.98

4
2

Overall Satisfaction - Customer Type: 2

4.98

4.71

4.44

4.17

3.90

3.62

3.35

3.08

2.81

2.54

2.26

1.99

1.72

0

95% CI Mean = 4.01 to 4.4
95% CI Sigma = 0.511126 to 0.792132
Anderson-Darling Normality Test:
A-Squared = 0.826259; P-value = 0.0302

Back to
Index
Graphical Tools:
Multiple Histograms &
Process Capability
Histogram and Process Capability Report
Room Service Delivery Time: Before Improvement (Baseline)
LSL = -10

Target = 0

USL = 10

160
140
120

Count = 725
Mean = 6.0036
Stdev (Overall) = 7.1616
USL = 10; Target = 0; LSL = -10
Capability Indices using Overall Standard Deviation
Pp = 0.47
Ppu = 0.19; Ppl = 0.74
Ppk = 0.19
Cpm = 0.36
Sigma Level = 2.02
Expected Overall Performance
ppm > USL = 288409.3
ppm < LSL = 12720.5
ppm Total = 301129.8
% > USL = 28.84%
% < LSL = 1.27%
% Total = 30.11%

100
80
60

Actual (Empirical) Performance
% > USL = 26.90%
% < LSL = 1.38%
% Total = 28.28%

40
20
0
Delivery Time Deviation

Histogram and Process Capability Report
Room Service Delivery Time: After Improvement
LSL = -10

Target = 0

USL = 10

Anderson-Darling Normality Test
A-Squared = 0.708616; P-value = 0.0641
Count = 725
Mean = 0.09732
Stdev (Overall) = 2.3856
USL = 10; Target = 0; LSL = -10
Capability Indices using Overall Standard Deviation
Pp = 1.40
Ppu = 1.38; Ppl = 1.41
Ppk = 1.38
Cpm = 1.40
Sigma Level = 5.53

160
140
120

Expected Overall Performance
ppm > USL = 16.5
ppm < LSL = 11.5
ppm Total = 28.1
% > USL = 0.00%
% < LSL = 0.00%
% Total = 0.00%

100
80
60
40

Actual (Empirical) Performance
% > USL = 0.00%
% < LSL = 0.00%
% Total = 0.00%

20
0
Delivery Time Deviation

Anderson-Darling Normality Test
A-Squared = 0.189932; P-value = 0.8991

Back to
Index
Graphical Tools:
Multiple Boxplots

5

Overall Satisfaction

Overall Satisfaction

5

4

3

2

1

4

3

2

1
1

2
Customer Type - Size of Customer: Large

3

1

2

3

Customer Type - Size of Customer: Small

Back to
Index
Graphical Tools:
Multiple Normal Probability
Plots

2

1

1
NSCORE

3

2

NSCORE

3

0

0

-1

-1

-2

-2

-3

-3
1

2

3

4

Overall Satisfaction - Customer Type: 1

5

6

2.1

2.6

3.1

3.6

4.1

4.6

5.1

5.6

6.1

Overall Satisfaction - Customer Type: 2

Back to
Index
Overall Satisfaction (Mean
Options)

Graphical Tools:
Multi-Vari Charts
4.634

4.634

4.634

4.634

4.134

4.134

4.134

4.134

3.634

3.634

3.634

3.634

3.134

3.134

3.134

3.134

2.634

2.634

2.634

2.634

2.134

2.134

2.134

2.134

1.634

1.634
#1

#2

#3

Standard Deviation

Customer Type - Size of Customer:
Large - Product Type: Consumer

1.634
#1

#2

#3

Customer Type - Size of Customer: Small Product Type: Consumer

1.634
#1

#2

#3

Customer Type - Size of Customer: Large Product Type: Manufacturer

#1

#2

#3

Customer Type - Size of Customer: Small Product Type: Manufacturer

1.00

1.00

1.00

1.00

0.80

0.80

0.80

0.80

0.60

0.60

0.60

0.60

0.40

0.40

0.40

0.40

0.20

0.20

0.20

0.20

0.00

0.00

0.00

#1

#2

#3

Customer Type - Size of Customer:
Large - Product Type: Consumer

#1

#2

#3

Customer Type - Size of Customer: Small Product Type: Consumer

0.00
#1

#2

#3

Customer Type - Size of Customer: Large Product Type: Manufacturer

#1

#2

#3

Customer Type - Size of Customer: Small Product Type: Manufacturer

Back to
Index
Graphical Tools:
Multiple Scatterplots with
Linear Regression
5.1
4.6

y = 0.5238x + 1.6066
R2 = 0.6864

5.1

y = 0.5639x + 1.822
R2 = 0.6994

4.6

Overall Satisfaction

Overall Satisfaction

4.1
3.6
3.1
2.6

4.1

3.6

3.1

2.1

2.6

1.6
1.1
1.01

1.51

2.01

2.51

3.01

3.51

Responsive to Calls - Customer Type: 1

4.01

4.51

2.1
1.88

2.38

2.88

3.38

3.88

4.38

4.88

Responsive to Calls - Customer Type: 2

Linear Regression with 95%
Confidence Interval and Prediction Interval

Back to
Index
y = 0.567x + 1.6103
R2 = 0.6827

3.7200

2.7200

1.7200
1.0000

2.0000

3.0000

4.0000

3.7200

2.7200

1.7200
1.4000

5.0000

Responsive to Calls
y = 1.2041x - 0.7127
R2 = 0.6827

2.0000

1.0000
1.7200 2.2200 2.7200 3.2200 3.7200 4.2200 4.7200

3.0000

2.0000

1.4000
1.7200 2.2200 2.7200 3.2200 3.7200 4.2200 4.7200

2.0000

3.0000

4.0000

5.0000

0.9600
1.7200 2.2200 2.7200 3.2200 3.7200 4.2200 4.7200

Overall Satisfaction

3.9600
y = 0.0799x + 2.9889
R2 = 0.0071

2.9600

1.9600

0.9600
1.0000

4.9600

y = 0.0893x + 3.57
R2 = 0.0071

3.0000

2.0000

1.9600

2.9600

3.9600

4.9600

Staff Knowledge

4.4000
y = 0.0428x + 3.6071
R2 = 0.0026
3.4000

2.4000

1.4000
0.9600

1.9600

2.9600

3.9600

4.9600

4.9600

2.0000

3.0000

4.0000

Responsive to Calls

5.0000

Staff Knowledge

1.9600

3.9600

Staff Knowledge

4.9600

Staff Knowledge

Staff Knowledge

2.9600

y = 0.303x + 2.5773
R2 = 0.1437

2.4000

1.4000
1.0000

2.9600

4.0000

1.0000
0.9600

4.4000

Responsive to Calls

4.9600

y = 0.1055x + 2.8965
R2 = 0.0059

3.4000

3.4000

Overall Satisfaction

3.9600

2.4000

Ease of Communications

2.4000

4.4000

1.9600

Staff Knowledge

Ease of Communications

Ease of Communications

Ease of Communications

Overall Satisfaction

3.4000

2.7200

5.0000
y = 0.4743x + 2.0867
R2 = 0.1437

4.0000

1.0000
1.4000

y = 0.0555x + 3.6181
R2 = 0.0059

3.7200

1.7200
0.9600

4.4000

Responsive to Calls

3.0000

y = 0.8682x + 0.4478
R2 = 0.5556

3.4000

5.0000

4.0000

4.4000

2.4000

4.7200

Ease of Communications

Responsive to Calls

Responsive to Calls

5.0000

y = 0.64x + 1.4026
R2 = 0.5556

4.7200

Overall Satisfaction

4.7200

Overall Satisfaction

Overall Satisfaction

Graphical Tools:
Scatterplot Matrix

3.9600
y = 0.0599x + 3.0732
R2 = 0.0026

2.9600

1.9600

0.9600
1.4000

2.4000

3.4000

4.4000

Ease of Communications

Back to
Index

Contenu connexe

Tendances

Chap 9 A Process Capability & Spc Hk
Chap 9 A Process Capability & Spc HkChap 9 A Process Capability & Spc Hk
Chap 9 A Process Capability & Spc Hk
ajithsrc
 
Statistical quality__control_2
Statistical  quality__control_2Statistical  quality__control_2
Statistical quality__control_2
Tech_MX
 
SPC WithAdrian Adrian Beale
SPC WithAdrian Adrian BealeSPC WithAdrian Adrian Beale
SPC WithAdrian Adrian Beale
Adrian Beale
 
Measurement & uncertainty pp presentation
Measurement & uncertainty pp presentationMeasurement & uncertainty pp presentation
Measurement & uncertainty pp presentation
simonandisa
 
Measurement System Analysis (MSA)
Measurement System Analysis (MSA)Measurement System Analysis (MSA)
Measurement System Analysis (MSA)
Ram Kumar
 

Tendances (20)

Measurement System Analysis - Module 1
Measurement System Analysis - Module 1Measurement System Analysis - Module 1
Measurement System Analysis - Module 1
 
Chap 9 A Process Capability & Spc Hk
Chap 9 A Process Capability & Spc HkChap 9 A Process Capability & Spc Hk
Chap 9 A Process Capability & Spc Hk
 
Statistical quality__control_2
Statistical  quality__control_2Statistical  quality__control_2
Statistical quality__control_2
 
Javier Garcia - Verdugo Sanchez - Six Sigma Training - W2 Simple Variance Ana...
Javier Garcia - Verdugo Sanchez - Six Sigma Training - W2 Simple Variance Ana...Javier Garcia - Verdugo Sanchez - Six Sigma Training - W2 Simple Variance Ana...
Javier Garcia - Verdugo Sanchez - Six Sigma Training - W2 Simple Variance Ana...
 
Measuremen Systems Analysis Training Module
Measuremen Systems Analysis Training ModuleMeasuremen Systems Analysis Training Module
Measuremen Systems Analysis Training Module
 
Javier Garcia - Verdugo Sanchez - Six Sigma Training - W2 Correlation and Reg...
Javier Garcia - Verdugo Sanchez - Six Sigma Training - W2 Correlation and Reg...Javier Garcia - Verdugo Sanchez - Six Sigma Training - W2 Correlation and Reg...
Javier Garcia - Verdugo Sanchez - Six Sigma Training - W2 Correlation and Reg...
 
Gage r&r
Gage r&rGage r&r
Gage r&r
 
Statistical process control ppt @ doms
Statistical process control ppt @ doms Statistical process control ppt @ doms
Statistical process control ppt @ doms
 
OpEx SPC Training Module
OpEx SPC Training ModuleOpEx SPC Training Module
OpEx SPC Training Module
 
Javier Garcia - Verdugo Sanchez - Six Sigma Training - W2 Chi Square Test
Javier Garcia - Verdugo Sanchez - Six Sigma Training - W2 Chi Square TestJavier Garcia - Verdugo Sanchez - Six Sigma Training - W2 Chi Square Test
Javier Garcia - Verdugo Sanchez - Six Sigma Training - W2 Chi Square Test
 
Process Capability shift over time
Process Capability shift over timeProcess Capability shift over time
Process Capability shift over time
 
Msa la
Msa laMsa la
Msa la
 
6.2 msa-gauge-r&r
6.2 msa-gauge-r&r6.2 msa-gauge-r&r
6.2 msa-gauge-r&r
 
02trainingmaterialformsa (1) 111030062223-phpapp02
02trainingmaterialformsa (1) 111030062223-phpapp0202trainingmaterialformsa (1) 111030062223-phpapp02
02trainingmaterialformsa (1) 111030062223-phpapp02
 
Six Sigma Statistical Process Control (SPC) Training Module
Six Sigma Statistical Process Control (SPC) Training ModuleSix Sigma Statistical Process Control (SPC) Training Module
Six Sigma Statistical Process Control (SPC) Training Module
 
Attribute MSA
Attribute MSAAttribute MSA
Attribute MSA
 
SPC WithAdrian Adrian Beale
SPC WithAdrian Adrian BealeSPC WithAdrian Adrian Beale
SPC WithAdrian Adrian Beale
 
Measurement & uncertainty pp presentation
Measurement & uncertainty pp presentationMeasurement & uncertainty pp presentation
Measurement & uncertainty pp presentation
 
Measurement systems analysis and a study of anova method
Measurement systems analysis and a study of anova methodMeasurement systems analysis and a study of anova method
Measurement systems analysis and a study of anova method
 
Measurement System Analysis (MSA)
Measurement System Analysis (MSA)Measurement System Analysis (MSA)
Measurement System Analysis (MSA)
 

En vedette

Unsur intrinsik cerpen
Unsur intrinsik cerpenUnsur intrinsik cerpen
Unsur intrinsik cerpen
Marina Dhewiy
 

En vedette (16)

Winning presentation at the DCU Research Day 2011
Winning presentation at the DCU Research Day 2011Winning presentation at the DCU Research Day 2011
Winning presentation at the DCU Research Day 2011
 
Control charts
Control chartsControl charts
Control charts
 
20 de ani in siberia
20 de ani in siberia20 de ani in siberia
20 de ani in siberia
 
DiseñArtes
DiseñArtesDiseñArtes
DiseñArtes
 
Sigma xl eula
Sigma xl eulaSigma xl eula
Sigma xl eula
 
a-neruda-ps-jaime-botello
a-neruda-ps-jaime-botelloa-neruda-ps-jaime-botello
a-neruda-ps-jaime-botello
 
Sigma xl getting_started
Sigma xl getting_startedSigma xl getting_started
Sigma xl getting_started
 
Stats tools
Stats toolsStats tools
Stats tools
 
My Presentation at the European Wound Management Conference 2013 in Copenhagen
My Presentation at the European Wound Management Conference 2013 in CopenhagenMy Presentation at the European Wound Management Conference 2013 in Copenhagen
My Presentation at the European Wound Management Conference 2013 in Copenhagen
 
RIOT - Il gioco da tavola
RIOT - Il gioco da tavolaRIOT - Il gioco da tavola
RIOT - Il gioco da tavola
 
Design of experiments
Design of experimentsDesign of experiments
Design of experiments
 
Trans presentation
Trans presentationTrans presentation
Trans presentation
 
Measurement system analysis
Measurement system analysisMeasurement system analysis
Measurement system analysis
 
Unsur intrinsik cerpen
Unsur intrinsik cerpenUnsur intrinsik cerpen
Unsur intrinsik cerpen
 
Templates & Calculators
Templates & CalculatorsTemplates & Calculators
Templates & Calculators
 
tips for a successful presentation
tips for a successful presentationtips for a successful presentation
tips for a successful presentation
 

Similaire à Graphical tools

Quality Management.ppt
Quality Management.pptQuality Management.ppt
Quality Management.ppt
ddelucy
 
Risk management Report
Risk management ReportRisk management Report
Risk management Report
NewGate India
 
quality and performance
quality and performancequality and performance
quality and performance
MEHAK GHAI
 

Similaire à Graphical tools (20)

Ch04
Ch04Ch04
Ch04
 
Six sigma11
Six sigma11Six sigma11
Six sigma11
 
Facility Location
Facility Location Facility Location
Facility Location
 
Process Capability for certificate course for marketing engineers online
Process Capability for certificate course for marketing engineers onlineProcess Capability for certificate course for marketing engineers online
Process Capability for certificate course for marketing engineers online
 
7 qc tools basic
7 qc tools basic7 qc tools basic
7 qc tools basic
 
Six sigma pedagogy
Six sigma pedagogySix sigma pedagogy
Six sigma pedagogy
 
Six sigma
Six sigma Six sigma
Six sigma
 
Quality Management.ppt
Quality Management.pptQuality Management.ppt
Quality Management.ppt
 
Six sigma case study-a good approach with example
Six sigma case study-a good approach with exampleSix sigma case study-a good approach with example
Six sigma case study-a good approach with example
 
Quality andc apability hand out 091123200010 Phpapp01
Quality andc apability hand out 091123200010 Phpapp01Quality andc apability hand out 091123200010 Phpapp01
Quality andc apability hand out 091123200010 Phpapp01
 
Six sigma
Six sigmaSix sigma
Six sigma
 
Dmaic
DmaicDmaic
Dmaic
 
Statistical process control ppt @ bec doms
Statistical process control ppt @ bec domsStatistical process control ppt @ bec doms
Statistical process control ppt @ bec doms
 
Risk management Report
Risk management ReportRisk management Report
Risk management Report
 
statistical quality control
statistical quality controlstatistical quality control
statistical quality control
 
SPC Training by D&H Engineers
SPC Training by D&H EngineersSPC Training by D&H Engineers
SPC Training by D&H Engineers
 
TQM
TQMTQM
TQM
 
Process Capability: Step 4 (Normal Distributions)
Process Capability: Step 4 (Normal Distributions)Process Capability: Step 4 (Normal Distributions)
Process Capability: Step 4 (Normal Distributions)
 
quality and performance
quality and performancequality and performance
quality and performance
 
Introduction to Gage R&R
Introduction to Gage R&RIntroduction to Gage R&R
Introduction to Gage R&R
 

Dernier

The basics of sentences session 3pptx.pptx
The basics of sentences session 3pptx.pptxThe basics of sentences session 3pptx.pptx
The basics of sentences session 3pptx.pptx
heathfieldcps1
 
1029-Danh muc Sach Giao Khoa khoi 6.pdf
1029-Danh muc Sach Giao Khoa khoi  6.pdf1029-Danh muc Sach Giao Khoa khoi  6.pdf
1029-Danh muc Sach Giao Khoa khoi 6.pdf
QucHHunhnh
 
Spellings Wk 3 English CAPS CARES Please Practise
Spellings Wk 3 English CAPS CARES Please PractiseSpellings Wk 3 English CAPS CARES Please Practise
Spellings Wk 3 English CAPS CARES Please Practise
AnaAcapella
 

Dernier (20)

Mehran University Newsletter Vol-X, Issue-I, 2024
Mehran University Newsletter Vol-X, Issue-I, 2024Mehran University Newsletter Vol-X, Issue-I, 2024
Mehran University Newsletter Vol-X, Issue-I, 2024
 
Spatium Project Simulation student brief
Spatium Project Simulation student briefSpatium Project Simulation student brief
Spatium Project Simulation student brief
 
ICT Role in 21st Century Education & its Challenges.pptx
ICT Role in 21st Century Education & its Challenges.pptxICT Role in 21st Century Education & its Challenges.pptx
ICT Role in 21st Century Education & its Challenges.pptx
 
Unit-V; Pricing (Pharma Marketing Management).pptx
Unit-V; Pricing (Pharma Marketing Management).pptxUnit-V; Pricing (Pharma Marketing Management).pptx
Unit-V; Pricing (Pharma Marketing Management).pptx
 
How to Create and Manage Wizard in Odoo 17
How to Create and Manage Wizard in Odoo 17How to Create and Manage Wizard in Odoo 17
How to Create and Manage Wizard in Odoo 17
 
Unit-IV- Pharma. Marketing Channels.pptx
Unit-IV- Pharma. Marketing Channels.pptxUnit-IV- Pharma. Marketing Channels.pptx
Unit-IV- Pharma. Marketing Channels.pptx
 
SKILL OF INTRODUCING THE LESSON MICRO SKILLS.pptx
SKILL OF INTRODUCING THE LESSON MICRO SKILLS.pptxSKILL OF INTRODUCING THE LESSON MICRO SKILLS.pptx
SKILL OF INTRODUCING THE LESSON MICRO SKILLS.pptx
 
The basics of sentences session 3pptx.pptx
The basics of sentences session 3pptx.pptxThe basics of sentences session 3pptx.pptx
The basics of sentences session 3pptx.pptx
 
Sociology 101 Demonstration of Learning Exhibit
Sociology 101 Demonstration of Learning ExhibitSociology 101 Demonstration of Learning Exhibit
Sociology 101 Demonstration of Learning Exhibit
 
Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...
Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...
Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...
 
Food safety_Challenges food safety laboratories_.pdf
Food safety_Challenges food safety laboratories_.pdfFood safety_Challenges food safety laboratories_.pdf
Food safety_Challenges food safety laboratories_.pdf
 
1029-Danh muc Sach Giao Khoa khoi 6.pdf
1029-Danh muc Sach Giao Khoa khoi  6.pdf1029-Danh muc Sach Giao Khoa khoi  6.pdf
1029-Danh muc Sach Giao Khoa khoi 6.pdf
 
ICT role in 21st century education and it's challenges.
ICT role in 21st century education and it's challenges.ICT role in 21st century education and it's challenges.
ICT role in 21st century education and it's challenges.
 
How to Manage Global Discount in Odoo 17 POS
How to Manage Global Discount in Odoo 17 POSHow to Manage Global Discount in Odoo 17 POS
How to Manage Global Discount in Odoo 17 POS
 
Graduate Outcomes Presentation Slides - English
Graduate Outcomes Presentation Slides - EnglishGraduate Outcomes Presentation Slides - English
Graduate Outcomes Presentation Slides - English
 
HMCS Max Bernays Pre-Deployment Brief (May 2024).pptx
HMCS Max Bernays Pre-Deployment Brief (May 2024).pptxHMCS Max Bernays Pre-Deployment Brief (May 2024).pptx
HMCS Max Bernays Pre-Deployment Brief (May 2024).pptx
 
FSB Advising Checklist - Orientation 2024
FSB Advising Checklist - Orientation 2024FSB Advising Checklist - Orientation 2024
FSB Advising Checklist - Orientation 2024
 
Dyslexia AI Workshop for Slideshare.pptx
Dyslexia AI Workshop for Slideshare.pptxDyslexia AI Workshop for Slideshare.pptx
Dyslexia AI Workshop for Slideshare.pptx
 
Spellings Wk 3 English CAPS CARES Please Practise
Spellings Wk 3 English CAPS CARES Please PractiseSpellings Wk 3 English CAPS CARES Please Practise
Spellings Wk 3 English CAPS CARES Please Practise
 
General Principles of Intellectual Property: Concepts of Intellectual Proper...
General Principles of Intellectual Property: Concepts of Intellectual  Proper...General Principles of Intellectual Property: Concepts of Intellectual  Proper...
General Principles of Intellectual Property: Concepts of Intellectual Proper...
 

Graphical tools

  • 1. Graphical Tools SigmaXL® Version 6.1 Basic and Advanced (Multiple) Pareto Charts EZ-Pivot/Pivot Charts Multiple Boxplots and Dotplots Multiple Normal Probability Plots (with 95% confidence intervals to ease interpretation of normality/non-normality) Run Charts (with Nonparametric Runs Test allowing you to test for Clustering, Mixtures, Lack of Randomness, Trends and Oscillation.) Multi-Vari Charts Basic Histogram Multiple Histograms and Descriptive Statistics (includes Confidence Interval for Mean and StDev., as well as Anderson-Darling Normality Test) Multiple Histograms and Process Capability (Pp, Ppk, Cpm, ppm, %) Scatter Plots (with linear regression and optional 95% confidence intervals and prediction intervals) Scatter Plot Matrix
  • 2. Graphical Tools: Multiple Pareto Charts 2 Customer Type - Customer Type: # 1 - Size of Customer: Large 6 4 2 Ordertakestoo-long Notavailable Wrongcolor Difficultto-order Returncalls 0 Customer Type - Customer Type: # 1 - Size of Customer: Small Ordertakestoo-long 10 8 6 4 2 0 Ordertakestoo-long 8 12 Notavailable 10 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% 14 Count 12 Count Customer Type - Customer Type: # 2 - Size of Customer: Large 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% 14 Notavailable 0 Ordertakestoo-long Notavailable Wrongcolor Difficultto-order Returncalls 0 4 Wrongcolor 2 6 Wrongcolor 4 8 Difficultto-order 6 10 Difficultto-order 8 12 Returncalls Count 10 Returncalls 12 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% 14 Count 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% 14 Customer Type - Customer Type: # 2 - Size of Customer: Small Back to Index
  • 3. Graphical Tools: EZ-Pivot/Pivot Charts – The power of Excel’s Pivot Table and Charts are now easy to use! Size of Customer (All) 70 Count of Major-Complaint 60 50 40 Customer Type 3 2 1 30 20 10 0 Difficult-to-order Not-available Order-takes-too-long Return-calls Wrong-color Major-Complaint Back to Index
  • 5. Basic Histogram Count = 100 Mean = 3.530 Stdev = 0.904031 Minimum = 1 45 25th Percentile (Q1) = 3 50th Percentile (Median) = 4 40 95% CI Mean = 3.351 to 3.709 95% CI Sigma = 0.793746 to 1.050191 35 Anderson-Darling Normality Test: A-Squared = 5.417 25 20 15 10 5 6.00 Loyalty - Likely to Recommend 5.00 4.00 3.00 2.00 0 1.00 Frequency 30 Back to Index
  • 6. Graphical Tools: Multiple Histograms & Descriptive Statistics 12 Overall Satisfaction - Customer Type: 1 10 Count = 31 Mean = 3.3935 Stdev = 0.824680 Range = 3.1 8 6 Minimum = 1.7200 25th Percentile (Q1) = 2.8100 50th Percentile (Median) = 3.5600 75th Percentile (Q3) = 4.0200 Maximum = 4.8 4 2 4.98 4.71 4.44 4.17 3.90 3.62 3.35 3.08 2.81 2.54 2.26 1.99 1.72 0 Overall Satisfaction - Customer Type: 1 95% CI Mean = 3.09 to 3.7 95% CI Sigma = 0.659012 to 1.102328 Anderson-Darling Normality Test: A-Squared = 0.312776; P-value = 0.5306 12 Overall Satisfaction - Customer Type: 2 10 Count = 42 Mean = 4.2052 Stdev = 0.621200 Range = 2.6 8 6 Minimum = 2.4200 25th Percentile (Q1) = 3.8275 50th Percentile (Median) = 4.3400 75th Percentile (Q3) = 4.7250 Maximum = 4.98 4 2 Overall Satisfaction - Customer Type: 2 4.98 4.71 4.44 4.17 3.90 3.62 3.35 3.08 2.81 2.54 2.26 1.99 1.72 0 95% CI Mean = 4.01 to 4.4 95% CI Sigma = 0.511126 to 0.792132 Anderson-Darling Normality Test: A-Squared = 0.826259; P-value = 0.0302 Back to Index
  • 7. Graphical Tools: Multiple Histograms & Process Capability Histogram and Process Capability Report Room Service Delivery Time: Before Improvement (Baseline) LSL = -10 Target = 0 USL = 10 160 140 120 Count = 725 Mean = 6.0036 Stdev (Overall) = 7.1616 USL = 10; Target = 0; LSL = -10 Capability Indices using Overall Standard Deviation Pp = 0.47 Ppu = 0.19; Ppl = 0.74 Ppk = 0.19 Cpm = 0.36 Sigma Level = 2.02 Expected Overall Performance ppm > USL = 288409.3 ppm < LSL = 12720.5 ppm Total = 301129.8 % > USL = 28.84% % < LSL = 1.27% % Total = 30.11% 100 80 60 Actual (Empirical) Performance % > USL = 26.90% % < LSL = 1.38% % Total = 28.28% 40 20 0 Delivery Time Deviation Histogram and Process Capability Report Room Service Delivery Time: After Improvement LSL = -10 Target = 0 USL = 10 Anderson-Darling Normality Test A-Squared = 0.708616; P-value = 0.0641 Count = 725 Mean = 0.09732 Stdev (Overall) = 2.3856 USL = 10; Target = 0; LSL = -10 Capability Indices using Overall Standard Deviation Pp = 1.40 Ppu = 1.38; Ppl = 1.41 Ppk = 1.38 Cpm = 1.40 Sigma Level = 5.53 160 140 120 Expected Overall Performance ppm > USL = 16.5 ppm < LSL = 11.5 ppm Total = 28.1 % > USL = 0.00% % < LSL = 0.00% % Total = 0.00% 100 80 60 40 Actual (Empirical) Performance % > USL = 0.00% % < LSL = 0.00% % Total = 0.00% 20 0 Delivery Time Deviation Anderson-Darling Normality Test A-Squared = 0.189932; P-value = 0.8991 Back to Index
  • 8. Graphical Tools: Multiple Boxplots 5 Overall Satisfaction Overall Satisfaction 5 4 3 2 1 4 3 2 1 1 2 Customer Type - Size of Customer: Large 3 1 2 3 Customer Type - Size of Customer: Small Back to Index
  • 9. Graphical Tools: Multiple Normal Probability Plots 2 1 1 NSCORE 3 2 NSCORE 3 0 0 -1 -1 -2 -2 -3 -3 1 2 3 4 Overall Satisfaction - Customer Type: 1 5 6 2.1 2.6 3.1 3.6 4.1 4.6 5.1 5.6 6.1 Overall Satisfaction - Customer Type: 2 Back to Index
  • 10. Overall Satisfaction (Mean Options) Graphical Tools: Multi-Vari Charts 4.634 4.634 4.634 4.634 4.134 4.134 4.134 4.134 3.634 3.634 3.634 3.634 3.134 3.134 3.134 3.134 2.634 2.634 2.634 2.634 2.134 2.134 2.134 2.134 1.634 1.634 #1 #2 #3 Standard Deviation Customer Type - Size of Customer: Large - Product Type: Consumer 1.634 #1 #2 #3 Customer Type - Size of Customer: Small Product Type: Consumer 1.634 #1 #2 #3 Customer Type - Size of Customer: Large Product Type: Manufacturer #1 #2 #3 Customer Type - Size of Customer: Small Product Type: Manufacturer 1.00 1.00 1.00 1.00 0.80 0.80 0.80 0.80 0.60 0.60 0.60 0.60 0.40 0.40 0.40 0.40 0.20 0.20 0.20 0.20 0.00 0.00 0.00 #1 #2 #3 Customer Type - Size of Customer: Large - Product Type: Consumer #1 #2 #3 Customer Type - Size of Customer: Small Product Type: Consumer 0.00 #1 #2 #3 Customer Type - Size of Customer: Large Product Type: Manufacturer #1 #2 #3 Customer Type - Size of Customer: Small Product Type: Manufacturer Back to Index
  • 11. Graphical Tools: Multiple Scatterplots with Linear Regression 5.1 4.6 y = 0.5238x + 1.6066 R2 = 0.6864 5.1 y = 0.5639x + 1.822 R2 = 0.6994 4.6 Overall Satisfaction Overall Satisfaction 4.1 3.6 3.1 2.6 4.1 3.6 3.1 2.1 2.6 1.6 1.1 1.01 1.51 2.01 2.51 3.01 3.51 Responsive to Calls - Customer Type: 1 4.01 4.51 2.1 1.88 2.38 2.88 3.38 3.88 4.38 4.88 Responsive to Calls - Customer Type: 2 Linear Regression with 95% Confidence Interval and Prediction Interval Back to Index
  • 12. y = 0.567x + 1.6103 R2 = 0.6827 3.7200 2.7200 1.7200 1.0000 2.0000 3.0000 4.0000 3.7200 2.7200 1.7200 1.4000 5.0000 Responsive to Calls y = 1.2041x - 0.7127 R2 = 0.6827 2.0000 1.0000 1.7200 2.2200 2.7200 3.2200 3.7200 4.2200 4.7200 3.0000 2.0000 1.4000 1.7200 2.2200 2.7200 3.2200 3.7200 4.2200 4.7200 2.0000 3.0000 4.0000 5.0000 0.9600 1.7200 2.2200 2.7200 3.2200 3.7200 4.2200 4.7200 Overall Satisfaction 3.9600 y = 0.0799x + 2.9889 R2 = 0.0071 2.9600 1.9600 0.9600 1.0000 4.9600 y = 0.0893x + 3.57 R2 = 0.0071 3.0000 2.0000 1.9600 2.9600 3.9600 4.9600 Staff Knowledge 4.4000 y = 0.0428x + 3.6071 R2 = 0.0026 3.4000 2.4000 1.4000 0.9600 1.9600 2.9600 3.9600 4.9600 4.9600 2.0000 3.0000 4.0000 Responsive to Calls 5.0000 Staff Knowledge 1.9600 3.9600 Staff Knowledge 4.9600 Staff Knowledge Staff Knowledge 2.9600 y = 0.303x + 2.5773 R2 = 0.1437 2.4000 1.4000 1.0000 2.9600 4.0000 1.0000 0.9600 4.4000 Responsive to Calls 4.9600 y = 0.1055x + 2.8965 R2 = 0.0059 3.4000 3.4000 Overall Satisfaction 3.9600 2.4000 Ease of Communications 2.4000 4.4000 1.9600 Staff Knowledge Ease of Communications Ease of Communications Ease of Communications Overall Satisfaction 3.4000 2.7200 5.0000 y = 0.4743x + 2.0867 R2 = 0.1437 4.0000 1.0000 1.4000 y = 0.0555x + 3.6181 R2 = 0.0059 3.7200 1.7200 0.9600 4.4000 Responsive to Calls 3.0000 y = 0.8682x + 0.4478 R2 = 0.5556 3.4000 5.0000 4.0000 4.4000 2.4000 4.7200 Ease of Communications Responsive to Calls Responsive to Calls 5.0000 y = 0.64x + 1.4026 R2 = 0.5556 4.7200 Overall Satisfaction 4.7200 Overall Satisfaction Overall Satisfaction Graphical Tools: Scatterplot Matrix 3.9600 y = 0.0599x + 3.0732 R2 = 0.0026 2.9600 1.9600 0.9600 1.4000 2.4000 3.4000 4.4000 Ease of Communications Back to Index