Based on the type I error, if a hypothesis test leads to the probability of a type I error decreasing, then the a. probability of incorrectly accepting the null hypothesis decreases.
A type I error refers to when we are are engaged in a hypothesis test and end up rejecting the Null hypothesis even though it is true.
If we are in hypothesis tests and the probability of a type 1 error decreases, then it means that the probability of us correctly rejecting the null hypothesis when it is false increases.
It also means that the probability of us correctly accepting the null hypothesis when it is true increases as well.
This can further be said as the probability of us accepting the null hypothsis when it is false, decreases. There are therefore less chances of us incorrectly accepting the null hypothesis.
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