Asked by animalla sindhu on Sep 29, 2024
Increasing the probability of a Type I error will increase the probability of a Type II error.
Type I Error
The incorrect rejection of a true null hypothesis in hypothesis testing, also known as a false positive.
Type II Error
The error made by failing to reject a false null hypothesis, also known as a false negative.
Increasing
A term indicating that something is growing or becoming larger in size, number, value, or quality.
- Comprehend the effects of altering the significance threshold on the chances of incurring Type I and Type II errors.
Learning Objectives
- Comprehend the effects of altering the significance threshold on the chances of incurring Type I and Type II errors.