Question
Type I error is when one is :
The correct answer is
Rejecting null hypothesis when it is true
Type I Error Definition
A Type I error occurs in statistical hypothesis testing when the null hypothesis (H0) is rejected, despite the fact that H0 is actually true.
This error is equivalent to a "false positive". The probability of making a Type I error is represented by the significance level, denoted as $\alpha$.
Evaluating the Options
- Option 1: Rejecting null hypothesis when it is true
This accurately defines a Type I error. - Option 2: Accepting null hypothesis when it is true
This represents a correct decision, not an error. - Option 3: Rejecting null hypothesis when it is not true
This is a correct decision, known as rejecting a false null hypothesis. - Option 4: Accepting null hypothesis when it is not true
This describes a Type II error (failing to reject a false null hypothesis).
Based on the definition, the correct statement is rejecting the null hypothesis when it is, in fact, true.
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Important Questions from Hypothesis testing
If α is the level of significance and if (1 − α) is increased, then the width of the confidence interval of mean:
The analysis of variance technique was introduced by:
The power of a test is:
The term ‘Analysis of variance’ was introduced by:
Which of the following can be applied as a goodness-of-fit test?
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