Alpha risk (α) is the risk of incorrectly deciding to reject the null hypothesis, HO. If the confidence interval is 95%, then the alpha risk is 5% or 0.05.

For example, there is a 5% chance that a part has been determined defective when it actually is not. One has observed, or made a decision, that a difference exists but there really is none. Or when the data on a control chart indicates the process is out of control but in reality the process is in control. Or the likelihood of detecting an effect when no effect is present.

Alpha risk is also called False Positive, Type I Error, or “Producers Risk”.

It is the probability of committing a Type I error – generally, the risk of incorrectly concluding that there is a difference when there is none. In other words it is the probability that a good product will be rejected as a bad product by the consumer. It calculates the probability of loss from (1) rejecting a batch which, in fact, should have been accepted, or (2) accepting a batch that, in fact, will be rejected by the customer. Alpha is the significance level of a test.

#### References

Alpha and Beta Risks. (n.d.). Retrieved June 22, 2021, from https://www.six-sigma-material.com/Alpha-and-Beta-Risks.html