The magnitude of type II error is determined by

Correct option is A

In statistical hypothesis testing, a Type II error (also known as a false negative) occurs when the null hypothesis is not rejected even though it is actually false. This means you fail to detect a real effect or difference when one exists.
The magnitude of a Type II error is denoted by β (Beta). It is the probability of making a Type II error and failing to reject a false null hypothesis. A lower β (Beta) indicates a lower likelihood of making a Type II error, meaning the test is more sensitive in detecting real effects.