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Solutions Manual for Applied Statistics in Business and Economics 2024 By David Doane (All Chapters 1-17, 100% Original Verified, A+ Grade)
All Chapters are arranged Reveres 17-1.Supplement Files Download Link at the end of PDF file. 1 / 4
ASBE 7e Solutions for Instructors
512
Chapter 17
Quality Management
17.1 a. Productivity is a ratio of output to input and measures efficiency.
- Quality control refers to methods used to ensure product or service quality.
- Process control refers to methods used to ensure process consistency and
conformance to process specifications.
Learning Objective: 17-1
17.2 From the modern perspective productivity and quality move in the same direction. When you improve quality you also improve productivity. In the past, the relationship was thought to be the inverse. People believed that to improve quality they must slow down processes which would decrease productivity. This is not the case if one considers that rework and scrap due to poor quality actually decrease productivity.
Learning Objective: 17-1
17.3 Common cause variation is normal and expected. It’s part of the process. Special cause variation is caused by something outside the normal process.
Learning Objective: 17-1
17.4 Zero variation is a lofty goal but not achievable. Variation will always exist. We can attempt to minimize variation but cannot eliminate all sources of variation.
Learning Objective: 17-1
17.5 Statisticians help organization define metrics used to measure quality and then help design data collection and process monitoring systems.
Learning Objective: 17-1
17.6 Students may name Deming, Shewhart, Ishikawa, Taguchi, and others they’ve heard of.
Learning Objective: 17-2
17.7 Deming’s 14 Points (abbreviated)
- Maintain constancy of purpose.
- Adopt a new philosophy.
- Don’t rely on inspection—design quality in.
- Don’t award contracts just on the basis of price.
- Continuous improvement.
- Institute training on the job.
- Supervision should help people do a better job.
- Drive out fear and create trust.
- Break down barriers between departments.
- Eliminate slogans, exhortations, and targets. 2 / 4
ASBE 7e Solutions for Instructors
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- Eliminate numerical goals.
- Remove barriers to pride in work.
- Continuing education for all.
- Act to accomplish the transformation.
See www.deming.org for a more detailed complete list.
Learning Objective: 17-2
17.8 a. A car dealership typically surveys their customers and might track the number of customers who respond that they were satisfied with their service.
- A bank might track the number of transactions that are error free. They might track
- The movie theater might track the time required to purchase a ticket or the number of
the time required to complete a transaction.
customer complaints.
Learning Objective: 17-3
17.9 SQC refers to a specific set of tools used to monitor, improve, and control product quality. Most of the tools rely on statistical techniques. SPC refers to the statistical tools used to monitor, improve, and control process characteristics.
Learning Objective: 17-3
17.10 Total Quality Management or TQM Business Process Redesign or BPR Continuous Quality Improvement or CQI Six Sigma or 6-sigma uses the DMAIC cycle (define, measure, analyze, improve, control) PDCA cycle (plan, do, check, act)
Learning Objective: 17-3
17.11 The improvement process is never-ending because once you eliminate one source of
variation you move to the next source of variation. Two cycles: PDCA (plan, do,
check, act) and DMAIC (define, measure, analyze, improve, control)
Learning Objective: 17-3
17.12 SERVQUAL
Reliability, Responsiveness, Assurance, Empathy, and Tangibles
Learning Objective: 17-3
17.13 Service blueprints and Service transaction analysis
Learning Objective: 17-3
17.14 Attribute control charts are for nominal data (e.g., proportion conforming) while variable control charts are for ratio or interval data (e.g., means).
Learning Objective: 17-4
17.15 a. Sampling frequency depends on cost and physical possibility of sampling. 3 / 4
ASBE 7e Solutions for Instructors
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- For normal data, small samples may suffice for a mean (Central Limit Theorem).
- Large samples may be needed for a proportion to get sufficient precision.
Learning Objective: 17-4
17.16 a. We can estimate using the sample standard deviation (s), or using 2 Rd where R is the average range and d2 is a control chart factor from Table 17.4, or using the average of the sample standard deviations of many samples (s ).
- The R is often used because we often know the range of values for our process. For
- MINITAB defaults to s because when a sample data set is provided it is the most
historical reasons, this method is still used frequently. Before the advent of computers it was easier to calculate than s.
direct way to estimate σ.
Learning Objective: 17-5
17.17 This is the Empirical Rule (see chapters 4 and 7):
- Within ± 1 standard deviations 68.26 percent of the time
- Within ± 2 standard deviations 95.44 percent of the time
- Within ± 3 standard deviations 99.73 percent of the time
Learning Objective: 17-5
17.18 Students may need to be reminded that “sigma” refers to the standard error of the mean n .Rule 1. Single point outside 3 sigma Rule 2. Two of three successive points outside 2 sigma on same side of centerline Rule 3. Four of five successive points outside 1 sigma on same side of centerline Rule 4. Nine successive points on same side of centerline
Learning Objective: 17-5
17.19 2
0.42
UCL 3 12.5 3 12.742
2.326 5
R x dn
= + = + =
2 0.42
LCL 3 12.5 3 12.258
2.326 5
R x dn
= − = − =
Learning Objective: 17-5
17.20 2
UCL 3 400 3 403
4n
= + = + =
2
LCL 3 400 3 397
4n
= − = − =
Learning Objective: 17-5
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