1. Setting the significance level at a very high cutoff (such as 15%) increases chances of what type of error?

2. Why do Type II errors concern scientists?

3. Why have confidence levels of significance been set at 5% and 1%?

4. Failing to reject the null hypothesis when the research hypothesis is true is referred to as what type of error?

5. What are three reasons that it is useful to understand statistical power?

6. By starting with the effect size and the desired level of power, a researcher can work backwards through the power formula to determine what?

7. In the situation where the null hypothesis is true, the distribution from which the sample was taken is the same as what distribution?

8. In statistical notation, p < .05 means that there is less than a 5% chance of making which type of error?

9. When the standard deviation of the original population is small, the experiment tends to have a __________ level of power.

10. Having a very small amount of overlap between the experimental and the comparison distributions __________ the power.