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Acceptance Sampling Definition
Arguably, acceptance sampling uses the appropriate tool for helping to make decisions like "Minitab". Statistical sampling is a procedure that decides whether the quality is acceptable or to reject a production lot of incoming material (involving the supplier and consumer material) as it has been a common quality control technique. This is used in industry and particularly in the military for contracts as well as procurement as it is usually done as products leave the factory or done sometimes within the factory.
Most often when a producer supplies a consumer a certain number of items and the decision whether to accept or reject the lot is made by determining the characteristics inspected number of defective items in a sample from the lot. The lot is received if the number of defects falls below a certain level that is the acceptance number otherwise the lot is rejected.
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It is a statistical measure that is used in quality control and so the company cannot test every one of its products due to either ruining the products or if there are many products. So acceptance sampling solves this by testing a sample of the product for defects where the process involves batch size and sample size as well as the number of defects acceptable in the batch.
This process allows a company's decision to determine the quality of ISO standard well-designed batch with a certain specified degree of statistical certainty without having to test every unit of product and then the statistical reliability of a sample is generally measured by a T-Test (t-statistic). Probability is considered a key factor in acceptance sampling, but it is not the only factor.
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However, this could be a grossly incorrect representation and more reliable conclusions can be made by increasing the specific sampling batch size higher than and greater than the sample size by doing more than just one test. By doing this it is possible to average the results and if it is done correctly, acceptance sampling is considered to be a very effective and important tool in quality control.
Suppose that there is a lot of size M where a random sample of size N < M is selected from the lot and an Acceptance number is determined and if it is found that the number of nonconforming is less than or equal to then the lot is accepted. If the number of nonconforming is greater than B then the lot is not accepted.
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