Controlling Type 1 error and encouraging reproducible research are important in clinical and translational research. These concepts are frequently discussed in lectures with mathematical language, analytic examples, and probability distributions that demonstrate the issues. However, first-time learners in biostatistics courses focusing on…

Although our students correctly define the terms p-value, Type I and Type II errors, they sometimes misinterpret results from real data. In this work we present an assignment intended to clear up these misconceptions.

Summary Employing a Wald confidence interval to test hypotheses about population proportions could lead to an increase in Type I or Type II errors unless the hypothesized value, p0, is used in computing its standard error rather than the sample proportion. Whereas the Wald confidence interval to estimate a population proportion uses the sample…