A researcher looks at the mean salaries of male and female electricians and decides based on the evidence that there is no difference between the two groups. Given that there was a failure to reject the null hypothesis, it is possible that a type II error was made.Given the type of error made in this situation, what could researchers do to reduce the risk of this error?Increase the sample size.Choose a .01 significance level, instead of a .05 significance level.
Question
A researcher looks at the mean salaries of male and female electricians and decides based on the evidence that there is no difference between the two groups. Given that there was a failure to reject the null hypothesis, it is possible that a type II error was made.Given the type of error made in this situation, what could researchers do to reduce the risk of this error?Increase the sample size.Choose a .01 significance level, instead of a .05 significance level.
Solution
To reduce the risk of a Type II error, researchers could indeed increase the sample size. A larger sample size can provide a more accurate representation of the population, which can help to detect a true effect if one exists.
Choosing a .01 significance level instead of a .05 significance level would make the test more stringent, reducing the risk of a Type I error (false positive), but it would not necessarily reduce the risk of a Type II error (false negative). In fact, it could potentially increase the risk of a Type II error because it requires a stronger evidence to reject the null hypothesis.
Another strategy to reduce the risk of a Type II error could be to increase the power of the test, which is the probability that the test correctly rejects the null hypothesis when the alternative hypothesis is true. This can be done by increasing the sample size, increasing the effect size (if possible), or using a more sensitive measurement instrument.
Similar Questions
Suppose the results indicate that the null hypothesis should not be rejected; thus, it is possible that a type II error has been committed.Given the type of error made in this situation, what could researchers do to reduce the risk of this error? Increase the sample size. Choose a 0.01 significance level instead of a 0.05 significance level.
Suppose that at the end of the five-year study described above, a greater proportion of the hormone-treated group have breast cancer and heart disease. This observed difference is statistically significant. Researchers are so alarmed by the results that the experiment is ended early to prevent further harm to the health of the women participating in the hormone group. Since the null hypothesis was rejected, it is possible researchers made a type I error.Given the type of error made in this situation, what could researchers do to reduce the risk of this error?
A researcher wants to avoid making a type II error. Which of the following actions would be the most effective in reducing the risk of a type II error? Increase the sample size. Choose an alpha level of 0.01. Choose an alpha level of 0.05.
Which of the following is not a way to deal with a type 2 error?Select one:a.Use a higher significance value (e.g. .1 rather than .05)b.Increase the sample sizec.Take the effect size into consideration.d.Control for extraneous variables
A researcher conducts a study with a large sample size and finds a statistically significant result. However, the effect size is very small. What is the implication of this finding? A. The study has high statistical power B. The results are practically significant C. The findings may not have real-world importance D. The study has a Type II Error
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