Asked by London Aldridge on Jun 10, 2024
Verified
Decision makers have most control over Type I error than Type II error.
Type I Error
The incorrect rejection of a true null hypothesis, often called a "false positive."
Type II Error
A statistical error that occurs when a false null hypothesis is not rejected, also known as a "false negative" finding.
- Understand the distinction between Type I and Type II errors, their consequences, and factors influencing their probabilities.
Verified Answer
EA
Elizabeth ArredondoJun 13, 2024
Final Answer :
True
Explanation :
Type I error occurs when the null hypothesis is rejected when it is actually true. Decision makers have control over Type I error through the choice of significance level or alpha level. The lower the significance level, the lower the probability of making a Type I error. In contrast, Type II error occurs when the null hypothesis is not rejected when it is actually false. Decision makers have less control over Type II error as it is affected by factors such as sample size, effect size, and variability.
Learning Objectives
- Understand the distinction between Type I and Type II errors, their consequences, and factors influencing their probabilities.