Question

The probability of rejecting null hypothesis when it is true is known as

• A. power of the test
• B. type I error
• C. type II error
• D. level of significance

Hint:

Remember: Type I error = rejecting a true null hypothesis (False Positive).
Type II error = failing to reject a false null hypothesis (False Negative).

Answer 1

The Correct Option is B

Step 1: Understanding the Concept:
In hypothesis testing, errors can occur.
Type I error is rejecting a true null hypothesis.

Step 2: Key Approach:
Recall the definitions of Type I and Type II errors.

Step 3: Detailed Explanation:
Option (A): Power of the test is the probability of rejecting a false null hypothesis (\(1 - \beta\)).
Option (B): Type I error is the probability of rejecting the null hypothesis when it is actually true.
This is also denoted by \(\alpha\), the level of significance.
Option (C): Type II error is the probability of failing to reject a false null hypothesis.
Option (D): Level of significance is the probability of making a Type I error.
Thus, the correct answer is (B) Type I error.
Type I error is also called the producer's risk.
The level of significance is the threshold, but the error itself is Type I.