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

How does the concept of statistical power relate to Type II Error?  A. High statistical power reduces the risk of Type II Error  B. High statistical power increases the risk of Type II Error  C. Type II Error is not influenced by statistical power  D. Statistical power is irrelevant in hypothesis testing

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.

A graduate student designs a research study. She hopes to show that the results of her experiment are statistically significant. What type of p-value indicates statistically significant results? A large p-value A small p-value The magnitude of a p-value has no impact on statistical significance.

.Question 18From many prior studies, a researcher expects an effect size of d = .57 for a new study, but a new colleague has suggested that an effect size of d = .42 is more reasonable given the change in the research design. If the effect size does decrease, then how would the expected power of the study change?1 pointPower would decrease.Type I errors would increase.Power would increase.β would decrease.

If an experiment sample size is too small, the size ________ the results