It should be clear at this point in the course, there are several sources of error that can effect statistical testing. What types of error can happen when making decisions based on test of hypotheses? Be specific. What does it mean if a researcher sets his/her alpha at .01, and rejects the null hypothesis? How is this different from setting the alpha at .05 and rejecting the null? How does the selected p-value influence the likelihood of finding a significant difference? What is meant (and not meant) when a researcher says a finding is "statistically significant"?