Question

Typically, when we decrease the probability of a type I error for a hypothesis test, we:

decrease the probability of a type II error

increase the probability of a type II error

Answer 1

Type 1 error

The rejection of null hypothesis when it is true is called type 1 error

Type 2 error

The acceptance of null hypothesis it is false.

Eg :- rejection of a lot of item when it is actually good is type 1 error

Whereas acceptance of a lot of item when the quality is actually poor is type 2 error.

It is easy to see that if the probability of type 1 error decrease then the type 2 error increases.

I.e. as the probability of rejection of good items decreases then there is probability of acceptance of actually bad items increases.

This problem is sorted out by the minimization techniques.