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2016-MGMT-6087-MODULE10-CHAPTER11-STATISTICALLYBASEDIMPROVEMENTS.ppt
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Statistically-Based
Quality Improvement
for Variables

QUALITY MANAGEMENT

WEEK 10- CHAPTER 11

Announcement

  • Student Satisfaction Surveys are now on-line

Agenda

  • Review of Last Week
  • 14 tools of Quality
  • Introduction to Statistical Controls
  • Assignment/Exercise


Strategic Quality Planning
Statistically-Based Quality Improvement for Variables

Statistical Fundamentals

Process Control Charts

Some Control Chart Concepts for Variables

Process Capability for Variables

Other Statistical Techniques in Quality Management

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Strategic Quality Planning
Statistically-Based Quality Improvement for Variables

Statistical Fundamentals

Statistical Thinking

All work occurs in a system of interconnected processes

All process have variation

(The amount … tends to be underestimated)

Understanding variation and reducing variation are important keys to success

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Question

Why do you statistics sometimes fail in the workplace?

Answer

Why do statistics sometimes fail in the workplace?

Lack of knowledge about the tools

General disdain for all things mathematical

Cultural barriers in a company

Statistical specialists have trouble communicating

Statistics generally are poorly taught, emphasizing mathematical development rather than application

People have a poor understanding of the scientific method

Organizations lack patience in collecting data. All decisions have to be made “yesterday”

Statistics are viewed as something to buttress an already-held opinion

People fear using statistics

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Answer

Why do statistics sometimes fail in the workplace?

Most people don’t understand random variation

Statistical tools often are reactive and focus on effects rather than causes

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Strategic Quality Planning
Statistically-Based Quality Improvement for Variables
Statistical Fundamentals

  • 11- *

Why do statistics sometimes fail in the workplace?

  • Statistics generally are poorly taught, emphasizing mathematical development rather than application
  • People have a poor understanding of the scientific method

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Strategic Quality Planning
Statistically-Based Quality Improvement for Variables
Statistical Fundamentals

  • 11- *

Why do statistics sometimes fail in the workplace? Organizations lack patience in collecting data. All decisions have to be made “yesterday” Statistics are viewed as something to buttress an already-held opinion People fear using statistics

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Strategic Quality Planning
Statistically-Based Quality Improvement for Variables
Statistical Fundamentals

  • 11- *

Why do statistics sometimes fail in the workplace? Most people don’t understand random variation Statistical tools often are reactive and focus on effects rather than causes

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Strategic Quality Planning
Statistically-Based Quality Improvement for Variables

Type I and Type II Errors Type I error Producers risk Probability that a good product will be rejected Type II error Consumers risk Probability that a nonconforming product will be available for sale

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Strategic Quality Planning
Statistically-Based Quality Improvement for Variables

Understanding Process Variation Random variation Centered around the mean Consistent amount of dispersion

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Strategic Quality Planning
Statistically-Based Quality Improvement for Variables

Understanding Process Variation Non-random variation “Special Causes” Results from some event Dispersion and average of the process are changing Process that is not repeatable

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Strategic Quality Planning
Statistically-Based Quality Improvement for Variables

Understanding Process Variation Process stability Random Variation Not nonrandom variation Process Charts Sampling Methods Samples are cheaper Take less time Less intrusive Destructive tests may destroy the sample

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Strategic Quality Planning
Statistically-Based Quality Improvement for Variables
Statistical Fundamentals

  • 11- *

Understanding Process Variation Sampling Methods Samples are cheaper Take less time Less intrusive Destructive tests may destroy the sample

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Strategic Quality Planning
Statistically-Based Quality Improvement for Variables

Random Samples Each piece has an equal chance of being selected for inspection Systematic Samples According to time or sequence Rational subgroups A group of data that is logically homogeneous Computing variation between subgroups

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Strategic Quality Planning
Statistically-Based Quality Improvement for Variables

Planning for Inspection What type of planning will be used Who will perform the inspection Who will use in-process inspection Sample size What critical attributes to be inspected are Where inspection should be performed

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Strategic Quality Planning
Statistically-Based Quality Improvement for Variables

Control Plans Required part of an ISO 9000 quality management system (QMS) Provide a documented, proactive approach to defining how to respond when process control charts show that a process is out of control

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Strategic Quality Planning
Statistically-Based Quality Improvement for Variables

  • 11- *

Control Plans

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Strategic Quality Planning
Statistically-Based Quality Improvement for Variables

Process Control Chart

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Strategic Quality Planning
Statistically-Based Quality Improvement for Variables

  • 11- *

Variables and attributes control charts Variable Attribute

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Strategic Quality Planning
Statistically-Based Quality Improvement for Variables

Variables and attributes control charts You must understand this generic process for implementing process charts You must know how to interpret process charts You need to know when different process charts are used You need to know how to computer limits for the different type of process chart

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Strategic Quality Planning
Statistically-Based Quality Improvement for Variables
Process Control Charts

  • 11- *

Variables and attributes control charts You need to know when different process charts are used You need to know how to computer limits for the different type of process chart

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Strategic Quality Planning
Statistically-Based Quality Improvement for Variables

A generalized procedure for developing process charts Identify critical operations in the process where inspection may be needed Identify critical product characteristics Determine whether the critical product characteristic is a variable or an attribute Select the appropriate process control chart Establish the control limits and use the chart to continually monitor and improve Update the limits when changes have been made to the process

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Strategic Quality Planning
Statistically-Based Quality Improvement for Variables
Process Control Charts

  • 11- *

A generalized procedure for developing process charts Select the appropriate process control chart Establish the control limits and use the chart to continually monitor and improve Update the limits when changes have been made to the process

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Strategic Quality Planning
Statistically-Based Quality Improvement for Variables

Understanding control charts A control chart is an application of hypothesis testing where: The null hypothesis is that the process is stable

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Strategic Quality Planning
Statistically-Based Quality Improvement for Variables

  • 11- *

Hypothesis Testing

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Strategic Quality Planning
Statistically-Based Quality Improvement for Variables

Process Chart

Strategic Quality Planning
Statistically-Based Quality Improvement for Variables

x and R charts

  • A variable control chart
  • Variables are:
  • X – process population average
  • X (x-bar) – mean or average
  • R - Range
  • MR – Moving Range
  • s – standard Deviation

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Strategic Quality Planning
Statistically-Based Quality Improvement for Variables

x charts

  • A variable control chart
  • x (x-bar) – mean or average
  • Used to measure average of characteristics
  • Select samples from process
  • Form samples into rational subgroups
  • Find average value of each subgroup
  • Divide sums of measurements by sample size
  • Plot on process control chart
  • R - Range

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Strategic Quality Planning
Statistically-Based Quality Improvement for Variables

R charts

  • A variable control chart
  • R – Range
  • Used to monitor dispersion of the process
  • Used in conjunction with x–bar chart
  • Collect samples from process
  • Organize into sub-groups
  • Usually 3 to 6 items
  • Compute range
  • Difference of high value in subgroup minus the low value
  • Plot on R chart

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Strategic Quality Planning
Statistically-Based Quality Improvement for Variables

x and R chart

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Strategic Quality Planning
Statistically-Based Quality Improvement for Variables

Next

After we have put the information into the charts

  • Compute centre line and control limits
  • Centre line is process average
  • Control Limits (upper and lower)
  • Usually three deviations away from centre line

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Strategic Quality Planning
Statistically-Based Quality Improvement for Variables

Completed x and R chart

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Strategic Quality Planning
Statistically-Based Quality Improvement for Variables

x and R chart calculation worksheet

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Strategic Quality Planning
Statistically-Based Quality Improvement for Variables

x and R chart calculation

worksheet for completed chart

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Strategic Quality Planning
Statistically-Based Quality Improvement for Variables

Examples where nonrandom situations occur

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Strategic Quality Planning
Statistically-Based Quality Improvement for Variables

Calculation worksheet and x

chart

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Strategic Quality Planning
Statistically-Based Quality Improvement for Variables
Process Control Charts

  • 11- *

x and R chart using excel

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Strategic Quality Planning
Statistically-Based Quality Improvement for Variables
Process Control Charts

Geometric and hypergeometric distributions

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Strategic Quality Planning
Statistically-Based Quality Improvement for Variables
Process Control Charts

  • 11- *

X and MR charts in excel

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Strategic Quality Planning
Statistically-Based Quality Improvement for Variables
Process Control Charts

  • 11- *

Example 11-3 using excel

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Strategic Quality Planning
Statistically-Based Quality Improvement for Variables
Process Control Charts

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Example 11-4 using excel

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Strategic Quality Planning
Statistically-Based Quality Improvement for Variables

x and S Charts

  • Used when R charts not precise enough
  • S = Standard Deviation
  • Used when variation in process is small
  • Do not compute ranges
  • Used in high-tech production

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Strategic Quality Planning
Statistically-Based Quality Improvement for Variables

Cusum Chart (Cumulative Sum Chart)

No independence between observations

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Strategic Quality Planning
Statistically-Based Quality Improvement for Variables

Choosing the correct variables control chart

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Strategic Quality Planning
Statistically-Based Quality Improvement for Variables

When a process is out of control some corrective action is needed: Identify the quality problem Form the correct team to evaluate and solve the problem Use structured brainstorming Brainstorm to identify potential solutions Eliminate the cause Restart the process Document the problem, root cause and solutions Communicate the results

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Strategic Quality Planning
Statistically-Based Quality Improvement for Variables
Some Control Chart Concepts for Variables

  • 11- *

When a process is out of control some corrective action is needed: Eliminate the cause Restart the process Document the problem, root cause and solutions Communicate the results

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Strategic Quality Planning
Statistically-Based Quality Improvement for Variables
Some Control Chart Concepts for Variables

  • 11- *

The effects of tampering with the process

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Strategic Quality Planning
Statistically-Based Quality Improvement for Variables
Process Capability for Variables

A highly capable process produces high volumes with few or no defects World-class levels of process capability are measured by parts per million (ppm) defect levels

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Strategic Quality Planning
Statistically-Based Quality Improvement for Variables
Process Capability for Variables

  • 11- *

Six Sigma A design program which emphasized engineering parts so that they are highly capable

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Strategic Quality Planning
Statistically-Based Quality Improvement for Variables
Process Capability for Variables

  • 11- *

Population and Sampling distributions for Class heights

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Strategic Quality Planning
Statistically-Based Quality Improvement for Variables
Process Capability for Variables

  • 11- *

Capability Studies Two purposes to determine whether a process is capable To determine whether a process consistently results in products that meet specifications To determine whether a process is in need of monitoring

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Strategic Quality Planning
Statistically-Based Quality Improvement for Variables
Process Capability for Variables

  • 11- *

Example 11-5 Proportion of Product Nonconforming

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Strategic Quality Planning
Statistically-Based Quality Improvement for Variables
Process Capability for Variables

  • 11- *

The difference between capability and stability A process is capable if individual products consistently meet specification A process is stable only if common variation is present in the process

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Strategic Quality Planning
Statistically-Based Quality Improvement for Variables
Other Statistical Techniques in Quality Management

  • 11- *

Interlinking

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Recap

You need to:

Know the generic process for developing charts

Be able to interpret charts

Be able to choose which chart to use

Formulas to derive the charts

Understand the purposes and assumptions underlying the charts

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Next Week

Read:

Chapter 13 – Six Sigma Management & Lean Tools

Quiz 4 is open and due

Final Group Case due in two weeks

  • 11- *

All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior written permission of the publisher.

Printed in the United States of America.

Copyright Statement

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Chart1

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10.8
11.4
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Sample Average
Sample Number
Value
Sample Averages for Ore-Ida UPC Code

Sheet1 (2)

412 PART 3 Implementing Quality
Sample # Sample Average
1 7 7 8 6 7 1 7 7 8 6 7 7
2 6 5 6 5 7 2 6 5 6 5 7 5.8
3 7 7 8 6 8 3 7 7 8 6 8 7.2
4 6 8 8 7 7 4 6 8 8 7 7 7.2
5 6 7 6 6 7 5 6 7 6 6 7 6.4
6 6 6 5 6 5 6 6 6 5 6 5 5.6
7 5 6 4 4 4 7 5 6 4 4 4 4.6
8 4 5 5 5 6 8 4 5 5 5 6 5
9 5 6 5 5 5 9 5 6 5 5 5 5.2
10 5 5 5 5 5 10 5 5 5 5 5 5
11 6 6 7 7 7 11 6 6 7 7 7 6.6
12 7 7 6 7 7 12 7 7 6 7 7 6.8
13 6 7 7 7 7 13 6 7 7 7 7 6.8
14 6 7 7 7 7 14 6 7 7 7 7 6.8
15 6 6 6 6 6 15 6 6 6 6 6 6
16 6 6 6 6 6 16 6 6 6 6 6 6
17 6 7 7 6 7 17 6 7 7 6 7 6.6
18 6 7 6 7 7 18 6 7 6 7 7 6.6
19 6 6 6 6 6 19 6 6 6 6 6 6
20 5 6 5 6 6 20 5 6 5 6 6 5.6
21 9 12 10 10 10 21 9 12 10 10 10 10.2
22 10 10 9 10 10 22 10 10 9 10 10 9.8
23 10 10 10 9 10 23 10 10 10 9 10 9.8
24 10 10 10 10 10 24 10 10 10 10 10 10
25 10 10 10 10 10 25 10 10 10 10 10 10
26 10 10 10 11 10 26 10 10 10 11 10 10.2
27 11 12 10 11 11 27 11 12 10 11 11 11
28 11 12 10 11 12 28 11 12 10 11 12 11.2
29 10 11 11 11 11 29 10 11 11 11 11 10.8
30 10 11 12 10 10 30 10 11 12 10 10 10.6
31 10 11 11 11 11 31 10 11 11 11 11 10.8
32 11 11 11 12 12 32 11 11 11 12 12 11.4
33 11 11 0 0 5 33 11 11 0 0 5 5.4
34 6 4 4 5 7 34 6 4 4 5 7 5.2
35 7 6 6 0 1 35 7 6 6 0 1 4
36 6 7 6 7 6 36 6 7 6 7 6 6.4
37 6 6 5 6 7 37 6 6 5 6 7 6
38 10 9 10 10 9 38 10 9 10 10 9 9.6
39 10 9 8 8 11 39 10 9 8 8 11 9.2
40 10 10 10 10 10 40 10 10 10 10 10 10
41 10 10 10 11 10 41 10 10 10 11 10 10.2
42 11 11 11 10 10 42 11 11 11 10 10 10.6
43 10 10 10 10 10 43 10 10 10 10 10 10
44 11 10 10 10 10 44 11 10 10 10 10 10.2
45 10 10 10 10 10 45 10 10 10 10 10 10
46 10 10 10 10 10 46 10 10 10 10 10 10
47 10 10 10 10 10 47 10 10 10 10 10 10
48 10 10 10 11 12 48 10 10 10 11 12 10.6
49 10 11 10 11 11 49 10 11 10 11 11 10.6
50 12 12 11 11 11 50 12 12 11 11 11 11.4
51 12 11 11 10 10 51 12 11 11 10 10 10.8
52 12 12 11 11 10 52 12 12 11 11 10 11.2
53 10 11 11 11 11 53 10 11 11 11 11 10.8
54 11 10 11 12 11 54 11 10 11 12 11 11
55 11 10 12 11 11 55 11 10 12 11 11 11
56 11 11 12 11 11 56 11 11 12 11 11 11.2
57 10 10 12 12 11 57 10 10 12 12 11 11
58 10 11 11 11 11 58 10 11 11 11 11 10.8
59 11 11 16 16 17 59 11 11 16 16 17 14.2
60 18 17 17 16 16 60 18 17 17 16 16 16.8
61 18 17 16 16 16 61 18 17 16 16 16 16.6
62 17 17 17 17 16 62 17 17 17 17 16 16.8
63 16 16 16 15 16 63 16 16 16 15 16 15.8
64 16 17 18 16 16 64 16 17 18 16 16 16.6
65 16 17 17 17 16 65 16 17 17 17 16 16.6
66 16 17 17 17 17 66 16 17 17 17 17 16.8
67 15 15 17 16 17 67 15 15 17 16 17 16
68 16 15 16 17 17 68 16 15 16 17 17 16.2
69 16 16 16 18 16 69 16 16 16 18 16 16.4
70 16 15 17 16 16 70 16 15 17 16 16 16
71 16 15 16 15 16 71 16 15 16 15 16 15.6
72 16 16 16 16 16 72 16 16 16 16 16 16
73 15 15 15 16 16 73 15 15 15 16 16 15.4
74 16 15 16 16 16 74 16 15 16 16 16 15.8
75 16 16 16 16 15 75 16 16 16 16 15 15.8
76 16 16 15 16 17 76 16 16 15 16 17 16
77 16 16 16 16 16 77 16 16 16 16 16 16
78 17 16 15 16 16 78 17 16 15 16 16 16
79 17 17 17 16 16 79 17 17 17 16 16 16.6
80 16 16 16 16 16 80 16 16 16 16 16 16

Sheet1 (2)

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Sample Average
Sample Number
Value
Sample Averages for Ore-Ida UPC Code

Sheet1

412 PART 3 Implementing Quality
Sample # Sample Average
1 7 7 8 6 7 1 7 7 8 6 7 7
2 6 5 6 5 7 2 6 5 6 5 7 5.8
3 7 7 8 6 8 3 7 7 8 6 8 7.2
4 6 8 8 7 7 4 6 8 8 7 7 7.2
5 6 7 6 6 7 5 6 7 6 6 7 6.4
6 6 6 5 6 5 6 6 6 5 6 5 5.6
7 5 6 4 4 4 7 5 6 4 4 4 4.6
8 4 5 5 5 6 8 4 5 5 5 6 5
9 5 6 5 5 5 9 5 6 5 5 5 5.2
10 5 5 5 5 5 10 5 5 5 5 5 5
11 6 6 7 7 7 11 6 6 7 7 7 6.6
12 7 7 6 7 7 12 7 7 6 7 7 6.8
13 6 7 7 7 7 13 6 7 7 7 7 6.8
14 6 7 7 7 7 14 6 7 7 7 7 6.8
15 6 6 6 6 6 15 6 6 6 6 6 6
16 6 6 6 6 6 16 6 6 6 6 6 6
17 6 7 7 6 7 17 6 7 7 6 7 6.6
18 6 7 6 7 7 18 6 7 6 7 7 6.6
19 6 6 6 6 6 19 6 6 6 6 6 6
20 5 6 5 6 6 20 5 6 5 6 6 5.6
21 9 12 10 10 10 21 9 12 10 10 10 10.2
22 10 10 9 10 10 22 10 10 9 10 10 9.8
23 10 10 10 9 10 23 10 10 10 9 10 9.8
24 10 10 10 10 10 24 10 10 10 10 10 10
25 10 10 10 10 10 25 10 10 10 10 10 10
26 10 10 10 11 10 26 10 10 10 11 10 10.2
27 11 12 10 11 11 27 11 12 10 11 11 11
28 11 12 10 11 12 28 11 12 10 11 12 11.2
29 10 11 11 11 11 29 10 11 11 11 11 10.8
30 10 11 12 10 10 30 10 11 12 10 10 10.6
31 10 11 11 11 11 31 10 11 11 11 11 10.8
32 11 11 11 12 12 32 11 11 11 12 12 11.4
33 11 11 0 0 5 33 11 11 0 0 5 5.4
34 6 4 4 5 7 34 6 4 4 5 7 5.2
35 7 6 6 0 1 35 7 6 6 0 1 4
36 6 7 6 7 6 36 6 7 6 7 6 6.4
37 6 6 5 6 7 37 6 6 5 6 7 6
38 10 9 10 10 9 38 10 9 10 10 9 9.6
39 10 9 8 8 11 39 10 9 8 8 11 9.2
40 10 10 10 10 10 40 10 10 10 10 10 10
41 10 10 10 11 10 41 10 10 10 11 10 10.2
42 11 11 11 10 10 42 11 11 11 10 10 10.6
43 10 10 10 10 10 43 10 10 10 10 10 10
44 11 10 10 10 10 44 11 10 10 10 10 10.2
45 10 10 10 10 10 45 10 10 10 10 10 10
46 10 10 10 10 10 46 10 10 10 10 10 10
47 10 10 10 10 10 47 10 10 10 10 10 10
48 10 10 10 11 12 48 10 10 10 11 12 10.6
49 10 11 10 11 11 49 10 11 10 11 11 10.6
50 12 12 11 11 11 50 12 12 11 11 11 11.4
51 12 11 11 10 10 51 12 11 11 10 10 10.8
52 12 12 11 11 10 52 12 12 11 11 10 11.2
53 10 11 11 11 11 53 10 11 11 11 11 10.8
54 11 10 11 12 11 54 11 10 11 12 11 11
55 11 10 12 11 11 55 11 10 12 11 11 11
56 11 11 12 11 11 56 11 11 12 11 11 11.2
57 10 10 12 12 11 57 10 10 12 12 11 11
58 10 11 11 11 11 58 10 11 11 11 11 10.8
59 11 11 16 16 17 59 11 11 16 16 17 14.2
60 18 17 17 16 16 60 18 17 17 16 16 16.8
61 18 17 16 16 16 61 18 17 16 16 16 16.6
62 17 17 17 17 16 62 17 17 17 17 16 16.8
63 16 16 16 15 16 63 16 16 16 15 16 15.8
64 16 17 18 16 16 64 16 17 18 16 16 16.6
65 16 17 17 17 16 65 16 17 17 17 16 16.6
66 16 17 17 17 17 66 16 17 17 17 17 16.8
67 15 15 17 16 17 67 15 15 17 16 17 16
68 16 15 16 17 17 68 16 15 16 17 17 16.2
69 16 16 16 18 16 69 16 16 16 18 16 16.4
70 16 15 17 16 16 70 16 15 17 16 16 16
71 16 15 16 15 16 71 16 15 16 15 16 15.6
72 16 16 16 16 16 72 16 16 16 16 16 16
73 15 15 15 16 16 73 15 15 15 16 16 15.4
74 16 15 16 16 16 74 16 15 16 16 16 15.8
75 16 16 16 16 15 75 16 16 16 16 15 15.8
76 16 16 15 16 17 76 16 16 15 16 17 16
77 16 16 16 16 16 77 16 16 16 16 16 16
78 17 16 15 16 16 78 17 16 15 16 16 16
79 17 17 17 16 16 79 17 17 17 16 16 16.6
80 16 16 16 16 16 80 16 16 16 16 16 16

Sheet1

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Sample Average
Sample Number
Value
Sample Averages for Ore-Ida UPC Code

Sheet2

Sheet3

024681012141618147101316192225283134374043464952555861646770737679ValueSample NumberSample Averages for Ore-Ida UPC CodeSample Average