QuestionSuppose the results indicate that the null hypothesis should be rejected; thus, it is possible that a type I error has been committed.
Given the type of error made in this situation, what could researchers do to reduce the risk of this error?
Instead of a .05 significance level, choose a .01 significance level
Increase the sample size.
Studdy Solution
STEP 1
1. A Type I error occurs when the null hypothesis is incorrectly rejected.
2. The significance level () is the probability of making a Type I error.
STEP 2
1. Understand the relationship between significance level and Type I error.
2. Understand the impact of sample size on statistical power and error rates.
3. Apply strategies to reduce the risk of a Type I error.
STEP 3
Understand that the significance level () is the threshold for rejecting the null hypothesis. A lower significance level means a lower probability of committing a Type I error.
STEP 4
Recognize that increasing the sample size can increase the power of a test, which is the probability of correctly rejecting a false null hypothesis. However, it does not directly affect the probability of a Type I error but can provide more accurate estimates.
STEP 5
To reduce the risk of a Type I error, researchers can:
- Choose a lower significance level, such as 0.01 instead of 0.05, which decreases the probability of rejecting the null hypothesis incorrectly.
- Increase the sample size to improve the accuracy and reliability of the test results, although this primarily affects Type II errors.
In conclusion, to reduce the risk of a Type I error, researchers should consider using a lower significance level and increasing the sample size for more reliable results.
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