Statistical Sampling
Statistical sampling involves selecting a representative subset of a population for inspection, allowing the project team to draw conclusions about overall quality without inspecting every item.
Explanation
Statistical sampling is a technique used in Control Quality when inspecting every deliverable or item is impractical, too costly, or destructive. Instead of testing 100% of items, a carefully selected sample is tested, and the results are used to make inferences about the quality of the entire population. The sample must be representative and of sufficient size to provide statistically valid conclusions.\n\nThe two main types of sampling are attribute sampling (the result either conforms or does not conform, such as pass/fail) and variable sampling (the result is measured on a continuous scale, such as dimensions or weight). The appropriate sample size and sampling method depend on the confidence level required, the acceptable defect rate, and the population size. Sampling plans such as those defined by ANSI/ASQ Z1.4 provide standardized approaches.\n\nStatistical sampling reduces the cost of quality control while still providing confidence in the quality of deliverables. It is particularly useful for large production runs, destructive testing scenarios, and situations where 100% inspection is too time-consuming. The trade-off is that sampling introduces a small risk of accepting defective items or rejecting acceptable batches.
Key Points
- •Used when 100% inspection is impractical or too costly
- •Attribute sampling: pass/fail. Variable sampling: measured on a scale
- •Sample must be representative and of adequate size
- •Reduces quality control costs while maintaining confidence in results
Exam Tip
Know the difference between attribute sampling (binary: conforms or does not) and variable sampling (measured on a continuous scale). The exam may test this distinction directly.
Frequently Asked Questions
Related Topics
Control Quality
Control Quality is the process of monitoring and recording the results of executing quality management activities to assess performance and ensure project outputs are complete, correct, and meet customer expectations.
Quality Metrics
Quality metrics are specific, measurable attributes of project deliverables or processes that describe what will be measured and how it will be measured during quality management activities.
Control Charts
A control chart is a graph used to study how a process changes over time, displaying data points plotted against upper and lower control limits to determine whether the process is in statistical control.
Check Sheets
A check sheet is a structured form used to collect and organize data in real time at the location where the data is generated, often used as a preliminary step for other quality analysis tools.
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Risk Register
The risk register is a project document that records the details of individual project risks, including their identification, analysis results, response plans, and current status.
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Stakeholder mapping is the visual representation of stakeholder relationships, influence, interest, or other attributes using grids, matrices, or diagrams to support analysis and engagement planning.
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Cost Performance Index (CPI)
Cost Performance Index (CPI) is an EVM efficiency metric that measures cost performance as the ratio of earned value to actual cost: CPI = EV / AC.
Schedule Performance Index (SPI)
Schedule Performance Index (SPI) is an EVM efficiency metric that measures schedule performance as the ratio of earned value to planned value: SPI = EV / PV.
Earned Value Management (EVM)
Earned Value Management (EVM) is a methodology that integrates scope, schedule, and cost data to assess project performance and progress objectively.
Power/Influence Grid
The power/influence grid is a stakeholder classification model that groups stakeholders based on their level of authority (power) and their active involvement or ability to affect the project (influence).
Part of
Quality Management
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