Sampling risk

Sampling risk

Sampling risk refers to the possibility that the results obtained from a sample may not accurately represent the entire population being examined. It is typically expressed as a percentage and represents the level of risk that the auditor is willing to accept that the sample may not reflect the actual values of the population. There are two types of sampling risk: producer's risk, where good products are incorrectly classified as nonconforming, and consumer's risk, where nonconforming products are incorrectly classified as conforming.From: Quality Auditing in Construction Projects [2019], What Every Manager Should Know about Quality [2019]

Auditing fundamentals

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Purchase Book

Published in Abdul Razzak Rumane, Quality Auditing in Construction Projects, 2019

Shirine L. Mafi

When a statistical sample is developed, the level of sampling risk that the auditor is willing to take is an important consideration. This is often referred as the sampling risk or the probability of committing a Type 1 error. For instance a sampling risk of 5% corresponds to an acceptable confidence of 95% meaning that the auditor is willing to accept the risk that 5 out of 100 (or 1 in 20) of the samples examined will not reflect the actual values that would be seen if the entire population was examined. Therefore there is always risk inherent in the sampling process.

Development of an adaptive sampling system based on a process capability index with flexible switching mechanism

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Journal Information

Published in International Journal of Production Research, 2022

To-Cheng Wang, Ming-Hung Shu

The validation and verification of product quality are indispensable for the supply chain channel to ensure upstream raw materials satisfy downstream stipulations (Kuei, Madu, and Lin 2008; Shu et al. 2022). The 100% inspection and acceptance sampling are two methods to obtain the products’ quality information for validation. Acceptance sampling is more attractive for practitioners because 100% inspection is costly and time-consuming. Practitioners in many industries, such as manufacturing (Aslam, Azam, and Jun 2015), food (Wang 2022), and reliability engineering (Fernández 2022), usually formulate an acceptance sampling plan (ASP) to implement acceptance sampling efficiently. The ASP can help practitioners control the sampling risk and provide a definite and efficient sample size and acceptance benchmark for lot disposition (Wang et al. 2022b).

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Auditing fundamentals

Development of an adaptive sampling system based on a process capability index with flexible switching mechanism