Category Inferential Statistics- Other

A Bayesian perspective on interpreting statistical significance

This site illustrates why a P-value cannot be interpreted in a vacuum. Suppose a hypothesis test results in . Even if the null were true, we would still see statistically significant results by chance alone about 5% of the time. But this is relatively infrequent. So if we see a small P-value, we hope that the null […]

Understanding assumptions and conditions

David Bock (one of the three coauthors of the textbook Intro Stats that we use in Math 150) has written an article about assumptions and conditions. His audience is AP Stats teachers, but we all can learn from what he has to say.