Type I / Alpha Error or Producer’s Risk and Type II / Beta Error or Consumer’s Risk

Think of a manufacturer that supplies certain electronics component to its consumers. The components, before they are shipped, undergo final inspection by the team assigned for the purpose.

This team needs to make the call whether to ship the component or not by doing an inspection.

This situation can be viewed as being similar to a test of hypothesis. The null hypothesis (Ho) in this case is that the component is not defective.

Ho: Component is not defective (and hence good)

H1: Component is defective

Suppose the team can make error in their judgment in determining whether the component is defective or otherwise.

Following four scenarios are possible in the above case.

Scenario 1 – the product is not defective but is rejected.

In this case Ho is true but rejected, which is a false positive. This is also called Type I or alpha error.

It is also called as producer’s risk as the producer pays for the scrap cost of a good component that is not shipped to the consumer assuming it was defective.

Scenario 2 – the product is defective but is accepted.

In this case Ho is false but accepted, which is a false negative. This is also called Type II or beta error.

It is also called as consumer’s risk as the consumer pays for a defective component that is shipped to her assuming it was not defective.

Scenario 3 – the product is not defective and is not rejected.

In this case Ho is true and not rejected, which is fine.

Scenario 4 – the product is defective and is rejected.

In this case Ho is false and rejected, which is fine.