The p value of a randomized controlled trial comparing Operation A (new procedure) and Operation B (gold standard) is 0.04. From this, we conclude that:
|A||Type II error is small and we could accept the findings of the study|
|B||The probability of false negative conclusion that operation A is better than Operation B, when in truth it is not is 4%|
|C||The power of the study to detect a difference between operation A and B is 96%|
|D||The probability of false positive conclusion that Operation A is better than Operation B when in truth it is not is 4%|
Ref: High Yield Biostatistics, Pg: 34-36 & Park PSM 22nd ed. 793
The probability of committing type I error is P value. Hence please remember it as a rule: Any question based on p-value, you only have to look at that option that describes a type I error or a false positive error. Any option beginning with type II error or β or false negative error or the power of the study can never be the answer to this question.
Type I Error: That is the rejection of null hypothesis in spite being true
Also called as false positive error i.e. in reality there is no difference but the study has concluded a difference.