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Participant Workbook
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© 2014 The Quality Group All Rights Reserved ver. 5.1 DATA AND GRAPHICAL ANALYSIS - 1© The Quality Group -Revised 8/20/09
© The Quality Group. All Rights Reserved – Revised 10/6/2014
Participant Workbook
Data and Graphical Analysis
Participant Workbook
My Notes
© 2014 The Quality Group All Rights Reserved ver. 5.1 DATA AND GRAPHICAL ANALYSIS - 2
© 1992, 1995, 2008, 2012, 2014 by The Quality Group. All rights reserved.Ver. 5.1 October, 2014
Terms of UseThis guide can only be used by those with a paid license to the corresponding course in the e-Learning curriculum produced and distributed by The Quality Group. No part of this Student Guide may be altered, reproduced, stored, or transmitted in any form by any means without the prior written permission of The Quality Group.
TrademarksAll terms mentioned in this guide that are known to be trademarks or service marks have been appropriately capitalized.
CommentsPlease address any questions or comments to your distributor or to The Quality Group at [email protected].
Participant Workbook
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Participant Workbook
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Participant Workbook
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Participant Workbook
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Participant Workbook
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© 2014 The Quality Group All Rights Reserved ver. 5.1 DATA AND GRAPHICAL ANALYSIS - 7
Time: 3 minutes
Participant Workbook
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.
Participant Workbook
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© 2014 The Quality Group All Rights Reserved ver. 5.1 DATA AND GRAPHICAL ANALYSIS - 9
Time: 2 minutes
Participant Workbook
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Participant Workbook
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Participant Workbook
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© 2014 The Quality Group All Rights Reserved ver. 5.1 DATA AND GRAPHICAL ANALYSIS - 12
Time: 3 minutes
Participant Workbook
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Participant Workbook
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Participant Workbook
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Time: 3 minutes
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Participant Workbook
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X
Time: 5 minutes
Participant Workbook
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Participant Workbook
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+1-2
Participant Workbook
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Participant Workbook
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Participant Workbook
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Participant Workbook
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Participant Workbook
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Participant Workbook
My Notes
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Participant Workbook
My Notes
© 2014 The Quality Group All Rights Reserved ver. 5.1 DATA AND GRAPHICAL ANALYSIS - 28
Control charts will be covered in detail in a future class. They are a very important tool for assessing stability of a process over time and have application in all phases of a project.
Participant Workbook
My Notes
© 2014 The Quality Group All Rights Reserved ver. 5.1 DATA AND GRAPHICAL ANALYSIS - 29
Participant Workbook
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Participant Workbook
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.
Participant Workbook
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Participant Workbook
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Participant Workbook
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© 2014 The Quality Group All Rights Reserved ver. 5.1 DATA AND GRAPHICAL ANALYSIS - 35
File: CASESTUDY_SHIPPING1
One of several issues identified by the project team is customer complaints due to shipping. The CTQ is on‐time shipment and the KPOV being measured is the number of days late.
The customers have requested that all shipments be on time and nothing be shipped earlier that 5 days.
Upper Spec:_________________ Lower Spec:___________________
Using the above file, calculate the days late from the SHIP DATE – DUE DATE using the Minitab calculator function Calc >> Calculator
Using the tools you learned in this module, analyze the data to determine if the variation in Cycle Time is due to shape, center, spread, stability, or some combination.Be prepared to share your results with the class.
TOOL USED OBSERVATIONS, CONCLUSIONS
Exercise – Putting It All Together
Participant Workbook
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Participant Workbook
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© 2014 The Quality Group All Rights Reserved ver. 5.1 DATA AND GRAPHICAL ANALYSIS - 37
Participant Workbook
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© 2014 The Quality Group All Rights Reserved ver. 5.1 DATA AND GRAPHICAL ANALYSIS - 38
Participant Workbook
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© 2014 The Quality Group All Rights Reserved ver. 5.1 DATA AND GRAPHICAL ANALYSIS - 39
The data represents shipping performance compared to due date.. Ship Delta is the difference between the ship date and due date measure in number of days. A negative value represents an early shipment, positive is late.
File: SHIPPING PERFORMANCE .xlsStat >> Basic Statistics >> Display Descriptive Statistics
Stat >> Basic Statistics >> Graphical Summary
Exercise 1 – Descriptive Statistics
Minitab 16
Participant Workbook
My Notes
© 2014 The Quality Group All Rights Reserved ver. 5.1 DATA AND GRAPHICAL ANALYSIS - 40
The data represents shipping performance compared to due date.. Ship Delta is the difference between the ship date and due date measure in number of days. A negative value represents an early shipment, positive is late.
File: SHIPPING PERFORMANCE .xlsGraphical Tools >> Histogram and Descriptive Statistics
Exercise 1 – Descriptive Statistics
SigmaXL
Participant Workbook
My Notes
© 2014 The Quality Group All Rights Reserved ver. 5.1 DATA AND GRAPHICAL ANALYSIS - 41
The data represents shipping performance compared to due date.. Ship Delta is the difference between the ship date and due date measure in number of days. A negative value represents an early shipment, positive is late.
File: SHIPPING PERFORMANCE .xlsAnalyze >> Distribution
Exercise 1 – Descriptive Statistics
JMP 10
Participant Workbook
My Notes
© 2014 The Quality Group All Rights Reserved ver. 5.1 DATA AND GRAPHICAL ANALYSIS - 42
Above upper spec = 1 ‐
Calc >> Probability Distributions >> Normal
Above upper spec = 1 - .8413 = .1587 or 15.87%
Below upper spec
Below Lower spec = .0228 or 2.28%
Amount out of spec = .1587 + .0228 = .1815 or 18.15%
Exercise 2 – Normal Probability
Minitab 16
Participant Workbook
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© 2014 The Quality Group All Rights Reserved ver. 5.1 DATA AND GRAPHICAL ANALYSIS - 43
Above upper spec = 1 ‐
Templates and Calculators >> Probability Distribution Calculators >> Normal
Exercise 2 – Normal Probability
SigmaXL
a) Percent of parts below the LSL - .0227 = 2.27%b) Percent of parts above the USL - .1587 = 15.87%c) Percent of parts out-of-spec - .1814 = 18.14%
Enter data
Participant Workbook
My Notes
© 2014 The Quality Group All Rights Reserved ver. 5.1 DATA AND GRAPHICAL ANALYSIS - 44
Above upper spec = 1 ‐
Launch JMP and create a new data table.Compute and display the normal probability.
1. Add one row to the data table2. Double-click the column header, "Column 1."3. In the dialog box that follows, select "New
Property --> Formula." Screenshot:4. Click "Edit Formula."5. In the dialog box that follows, double-click on
the words, "no formula." Enter "Normal Distribution(1.0)" Note: JMP requires that the user enter a z-value rather than x, mean, and standard deviation.
6. Note: When you finish editing the function, JMP will display it in a graphically-editable form. Functions can also be entered graphically using the "Functions" list and the arithmetic buttons. This approach is more intuitive, though more time-consuming. The "Normal Distribution" function is found under "Probability" when the functions are shown grouped.
7. Click "OK" to close the function dialog box. 8. Click "OK" in the column properties dialog box. 9. Repeat Step 5 and enter (-2.0)
JMP computes the probability and displays it in the first
row of Column 1.Above upper spec = 1 - .8413 = .1587 or 15.87%
Below Lower spec = .0228 or 2.28%
Amount out of spec = .1587 + .0228 = .1815 or 18.15%
Exercise 2 – Normal Probability
JMP 10
Participant Workbook
My Notes
© 2014 The Quality Group All Rights Reserved ver. 5.1 DATA AND GRAPHICAL ANALYSIS - 45
File: Pareto.mtwStat >> Quality Tools >> Pareto Chart
A project is looking at the number of discrepancies in company travel expense reports with the intent of reducing the cycle time to process the expenses.
Exercise 3 – Pareto Diagram
Minitab 17
Participant Workbook
My Notes
© 2014 The Quality Group All Rights Reserved ver. 5.1 DATA AND GRAPHICAL ANALYSIS - 46
A project is looking at the number of discrepancies in company travel expense reports with the intent of reducing the cycle time to process the expenses.
File: Pareto.xlsGraphical Tools >> Basic Pareto Chart
Exercise 3 – Pareto Diagram
SigmaXL
Participant Workbook
My Notes
© 2014 The Quality Group All Rights Reserved ver. 5.1 DATA AND GRAPHICAL ANALYSIS - 47
File: Pareto.mtwAnalyze >> Quality and Process >> Pareto Plot
A project is looking at the number of discrepancies in company travel expense reports with the intent of reducing the cycle time to process the expenses.
Exercise 3 – Pareto Diagram
JMP 10
Participant Workbook
My Notes
© 2014 The Quality Group All Rights Reserved ver. 5.1 DATA AND GRAPHICAL ANALYSIS - 48
Construct a Time Series Plot (Run Chart) for shipping performance
File: SHIPPING PERFORMANCE .MTWGraph >> Time Series Plot >> Simple
Exercise 4 – Time Series Plot
Minitab 17
Recall the histogram from an earlier exercise which shows a distribution which appears to be normal.
What additional information do you now have about this process?
Participant Workbook
My Notes
© 2014 The Quality Group All Rights Reserved ver. 5.1 DATA AND GRAPHICAL ANALYSIS - 49
Construct a Time Series Plot (Run Chart) for shipping performance
File: SHIPPING PERFORMANCE .MTWGraphical Tool >> Run Chart
Exercise 4 – Time Series Plot
SigmaXL
Recall the histogram from an earlier exercise which shows a distribution which appears to be normal.
What additional information do you now have about this process?
Participant Workbook
My Notes
© 2014 The Quality Group All Rights Reserved ver. 5.1 DATA AND GRAPHICAL ANALYSIS - 50
Construct a Time Series Plot (Run Chart) for shipping performance
File: SHIPPING PERFORMANCE .MTWAnalyze >> Quality and Process >> Control Chart >> Run Chart
Exercise 4 – Time Series Plot
JMP 10
Recall the histogram from an earlier exercise which shows a distribution which appears to be normal.
What additional information do you now have about this process?
Participant Workbook
My Notes
© 2014 The Quality Group All Rights Reserved ver. 5.1 DATA AND GRAPHICAL ANALYSIS - 51
Construct a Time Series Plot (Run Chart) for shipping performance
File: SHIPPING PERFORMANCE .MTWStat >> Control Charts >> Charts for Individuals >> ImR
Exercise 5 – Control Chart – Individual and Moving Range
Minitab 17
Control charts will be covered in detail in a later module
Tests for Special causesCTL‐E to return to dialog boxImR Options Tests
Participant Workbook
My Notes
© 2014 The Quality Group All Rights Reserved ver. 5.1 DATA AND GRAPHICAL ANALYSIS - 52
Construct a Time Series Plot (Run Chart) for shipping performance
File: SHIPPING PERFORMANCEControl Charts >> Individuals & Moving Range
Exercise 5 – Control Chart – Individual and Moving Range
SigmaXL
Control charts will be covered in detail in a later module
Participant Workbook
My Notes
© 2014 The Quality Group All Rights Reserved ver. 5.1 DATA AND GRAPHICAL ANALYSIS - 53
Construct a Time Series Plot (Run Chart) for shipping performance
File: SHIPPING PERFORMANCE .MTWAnalyze >> Quality and Process >> Control Chart >> IR
Exercise 5 – Control Chart – Individual and Moving Range
JMP 10
Control charts will be covered in detail in a later module
Tests for Special causes
Participant Workbook
My Notes
© 2014 The Quality Group All Rights Reserved ver. 5.1 DATA AND GRAPHICAL ANALYSIS - 54
Selling price for used cars of a particular model and option package were captured. Construct a scatter plot to see the relationship between the 2 variables.
This is typical of data collected in Excel and it will need to be stacked by rows.Create columns Age (yrs) and Car Price
Data >> Stack >> Stack Rows
Graph >> Scatter Plot, Simple
File: carprices.xls
Exercise 6 – Scatter Diagrams
Minitab 17
Participant Workbook
My Notes
© 2014 The Quality Group All Rights Reserved ver. 5.1 DATA AND GRAPHICAL ANALYSIS - 55
Selling price for used cars of a particular model and option package were captured. Construct a scatter plot to see the relationship between the 2 variables.
Data was collected for 4 cars at each age. This is typical of data collected in Excel and it will need to be stacked by rows.
Data Manipulation >> Stack Subgroups Across Rows
File: carprices.xls
Exercise 6 – Scatter Diagrams
SigmaXL
Graphical Tools >> Scatter Plots
Participant Workbook
My Notes
© 2014 The Quality Group All Rights Reserved ver. 5.1 DATA AND GRAPHICAL ANALYSIS - 56
Selling price for used cars of a particular model and option package were captured. Construct a scatter plot to see the relationship between the 2 variables.
This is typical of data collected in Excel and it will need to be transposed by rows.Create columns Age (yrs) and Car PriceTables >> Transpose
File: carprices.xls
Exercise 6 – Scatter Diagrams
JMP 10
Change to Car Price
Analyze >> Fit Y by X
Participant Workbook
My Notes
© 2014 The Quality Group All Rights Reserved ver. 5.1 DATA AND GRAPHICAL ANALYSIS - 57
Exercise 7 – Putting It All Together - Solution
The histogram shows a distribution which appears “normal”’ or bell=shaped. However, the P-Value for the normality test (P less than .05 means non-normal) shows a possible bi-modal distribution. Since the sample size is large (>30) there is not much tolerance for minor departures from normality. This passes the “eyeball” test so assume normality and go on, but look for reasons for this distribution
Percent above upper spec = 1 - .802 = .198
Percent below lower spec = .250
Total out of spec = .198 + .250 = .448or 44.8% defective
Minitab 17
NOTE – the non-statistical thinker would look at the data and note that the mean is less than zero, and might “observe” that the average shipping time is actually early – so what’s the problem?
Participant Workbook
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© 2014 The Quality Group All Rights Reserved ver. 5.1 DATA AND GRAPHICAL ANALYSIS - 58
Exercise 7 – Putting It All Together - Solution
A box plot using ship day of the week as a grouping variable shows a possible source of the clustering. Shipments on Thursday and Friday tend to be later than the rest of the week.
Minitab 17
The run chart shows a cyclic variation. The P-values (less than .05 is significant) show that the data is clustered and shows a lack of randomness. This could account for the abnormality with the distribution.
Participant Workbook
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© 2014 The Quality Group All Rights Reserved ver. 5.1 DATA AND GRAPHICAL ANALYSIS - 59
Exercise 7 – Putting It All Together - Solution
Looking at the Order Entry data, a Pareto chart shows that “No Problem” has the largest number –nothing interesting here.
A Box Plot using status as the grouping variable shows that pricing is the biggest contributor to the data entry time. Credit and new part also contribute.
Minitab 17
Participant Workbook
My Notes
© 2014 The Quality Group All Rights Reserved ver. 5.1 DATA AND GRAPHICAL ANALYSIS - 60
Exercise 7 – Putting It All Together - Solution
The histogram shows adistribution which appears“normal”’ or bell=shaped.However, the P-Value forthe normality test (P lessthan .05 means non-normal) shows a possiblebi-modal distribution. Sincethe sample size is large(>30) there is not muchtolerance for minordepartures from normality.This passes the “eyeball”test so assume normalityand go on, but look forreasons for this distribution
The histogramshows a distributionwhich appears“normal”’ orbell=shaped.However, the P-Value for thenormality test (P lessthan .05 means non-normal) shows apossible bi-modaldistribution. Sincethe sample size islarge (>30) there isnot much tolerancefor minor departuresfrom normality.
SigmaXL
Participant Workbook
My Notes
© 2014 The Quality Group All Rights Reserved ver. 5.1 DATA AND GRAPHICAL ANALYSIS - 61
Exercise 7 – Putting It All Together - Solution
Fri Mon Thurs Tues Wed‐13
‐11
‐9
‐7
‐5
‐3
‐1
1
3
5
7
*Day
s L
ate
Ship Day
The run chart shows a cyclic variation. The P-values (less than .05 is significant) show that the data is clustered and shows a lack of randomness.
A box plot using ship day of the week as a grouping variable shows a possible source of the clustering. Shipments on Thursday and Friday tend to be later than the rest of the week.
SigmaXL
Participant Workbook
My Notes
© 2014 The Quality Group All Rights Reserved ver. 5.1 DATA AND GRAPHICAL ANALYSIS - 62
Exercise 7 – Putting It All Together - Solution
no problem new part credit pricing
250 25 18 14
Cumulative Sum 0.814332248 0.895765472 0.954397394 1
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
0
50
100
150
200
250
300
Count
status
credit new part no problem pricing0
2
4
6
8
10
12
Dat
a E
ntr
y T
ime
(hrs
)
status
Looking at the OrderEntry data, a Paretochart shows that “NoProblem” has thelargest number –nothing interestinghere.
A Box Plot using status asthe grouping variableshows that pricing is thebiggest contributor to thedata entry time. Credit andnew part also contribute.
SigmaXL