Alpha and Beta Risk in Quality Control

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Alpha and Beta Risk. Please explain these terms in relation to Quality Control. What is meant and how are these terms used? Why are they important? What are Alpha and Beta Risk An Alpha error is the probability of rejecting a true null hypothesis. A Beta error is the probability of failing to reject a false null hypothesis. The Alpha and Beta risk is the amount of risk that the researcher is willing to take in accepting or rejecting a certain hypothesis. Usually the risk is 0.05%; which means that there is a 5% chance that one's hypothesis is incorrect. Alpha Risk Alpha risk is the risk of rejecting the true null hypothesis. For instance, the researcher decides to test whether a certain part is defective. The hypothesis is that the part is not defective. The null hypothesis states that the part is defective. The researcher incorrectly rejects the null hypothesis thereby committing the Alpha risk and releasing a defective product to the public. Alpha error is also called 'false positive' or 'Type 1' Error. Beta Risk Beta risk is failing to reject the false null hypothesis. Returning to the researcher, the null hypothesis declares the part to be defective, but this time the null hypothesis is, in reality, incorrect. The researcher, having erred in his research incorrectly accepts the null hypothesis as true when in fact it is not. As a result, a non-defective product is declared defective when, in fact, it is not. Beta risk is also called False Negative or
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