Asked by Shelby Henderson on Jun 08, 2024
Verified
Type II error is typically greater for two-tailed hypothesis tests than for one-tailed tests.
Type II Error
The error that occurs when a statistical test fails to reject a false null hypothesis, mistakenly indicating that a difference or effect does not exist.
Two-Tailed
Refers to a hypothesis test where the area of interest spans both tails of the distribution, allowing for testing of differences in both directions.
One-Tailed
A hypothesis test where the area of interest is only on one side of the distribution, testing for a direction-specific outcome.
- Understand the consequences of committing Type I and Type II errors during the hypothesis testing process.
- Comprehend the factors involved in selecting between one-tailed and two-tailed tests.
Verified Answer
AB
Alyssia BooneJun 15, 2024
Final Answer :
False
Explanation :
A Type II error, or the probability of failing to reject a false null hypothesis, is not inherently greater for two-tailed tests compared to one-tailed tests. The distinction primarily affects the distribution of the critical region(s) for rejecting the null hypothesis, not directly the probability of a Type II error, which also depends on the actual effect size, sample size, and chosen significance level.
Learning Objectives
- Understand the consequences of committing Type I and Type II errors during the hypothesis testing process.
- Comprehend the factors involved in selecting between one-tailed and two-tailed tests.