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Quiz, Data comparisons and uncertainty.

By Johan van Schalkwyk / November 6, 2020

Data comparisons and uncertainty: a roadmap for gaining in competence and improving the reliability of results.

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Question 1 of 10

1. Question
What is accreditation?
- Only practical proof of a laboratory’s assigned level of confidence (and competence).
- Accepted proof of a laboratory’s assigned level of confidence (and competence).
- Only academic proof is acceptable.
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Question 2 of 10

2. Question
What are the most appropriate methods for demonstrating continuous improvement in a laboratory?
- Inter-laboratory comparisons and evaluating uncertainties.
- Mentor reports and formal tests.
- Recommendations by line managers.
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Question 3 of 10

3. Question
What ISO standard is most commonly used for the accreditation of testing and calibration laboratories?
- ISO 14000
- ISO 17025
- ISO 14001
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Question 4 of 10

4. Question
What recommended method is used by calibration laboratories for evaluating measurement uncertainties?
- ISO Guide 98-3 (GUM).
- ISO 9001:2000 QMS
- ISO 4001 (NQA)
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Question 5 of 10

5. Question
State 4 ways in which a laboratory can monitor trends and deviations?
- a) taking part in inter-laboratory comparisons; b) regular checks of equipment used; c) comparing results obtained using different methods; d) assessing correlation of results for the object tested/calibrated with results for an object with different characteristics.
- There are no stages, it depends on the scope of work.
- a) taking part in the drafting of outcomes; b) test the equipment being used; c) comparing results obtained using different methods; d) document the results for an object with different characteristics.
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Question 6 of 10

6. Question
What is the aim of an inter-laboratory comparison and how are measurement results compared?
- a) for a lab to protect its results from other labs; b) for a lab to check the quality of the results; c) to check competence of labs by comparing results .(competitive advantage). Measurement results are documented with reference values obtained by a leading laboratory or consensus mean values.
- a) for a lab to position/check its results with respect to other labs; b) for a lab to check if its practices lead to consistent results; c) to check competence of labs by comparing results (i.e. the obtained values and uncertainties). Measurement results are compared with reference values obtained by a reference laboratory or consensus mean values.
- The aim is to benchmark your results agains your competitors results. The aim is to find a competitive advantage. Measurement results are compared with reference values obtained by a competitors laboratory or consensus mean values.
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Question 7 of 10

7. Question
What 2 types of methods are detailed in the GUM for determining uncertainty components?
- Type A; makes use of statistical analysis. Type B; uncertainty components are determined using techniques not based on statistical methods.
- Type A; makes use of comparative analysis. Type B; uncertainty components are determined using techniques based on statistical methods.
- Type A; makes use of statistical analysis. Type B; uncertainty components are determined using ISO standards.
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Question 8 of 10

8. Question
What are the 2 main models used for evaluating uncertainties?
- A physical model and a statistical model.
- A theoretical model and a statistical model.
- A flawed model and a statistical model.
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Question 9 of 10

9. Question
What are the 2 key performance indicators used for monitoring internal data comparisons?
- Reports or charts and a full external review/report.
- Control charts and Internal Normalized Mean Square Error (INMSE).
- Controlled interviews and observation of activities.
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Question 10 of 10

10. Question
What are the 2 key performance indicators used for monitoring external data comparisons and when are results considered to be satisfactory/good?
- a) External Normalized Mean Square Errors (ENMSE); If ENMSE < 1, the result is satisfactory. b) Z-score; if IZ-scoreI < 2, the result is “good”.
- a) External guidelines ref. ISO; No errors allowed. b) Z-score; if IZ-scoreI < 1, the result is “good”.
- a) External Normalized Mean Square Errors (ENMSE); If ENMSE < 5, the result is satisfactory. b) Z-score; if IZ-scoreI < 5, the result is “good”.
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