You can detect errors in your code using if statements, as we did in the first post, or you can detect them using the try-except structure, as we did in the second and third posts. With both of these approaches, we used the print command to provide the user with some information about the error and the sys.exit() command to
Read more
P values and hypothesis testing methods are frequently misused in clinical and experimental research, perhaps because of the misconception that they provide simple, objective tools to separate true from untrue facts. In a new paper, the cardiologist Daniel Mark and statisticians Kerry Lee and Frank Harrell explain the role and limitations of p values and hypothesis tests in clinical research.
Read more
I recently highlighted a symposium that was held to improve the reproducibility of biomedical research. The published report includes a discussion on strategies that can help improve research practice and research reproducibility. Statistics: continuing education opportunities Stakeholders at the conference highlighted the need for continuing education opportunities in statistics. Continuing education should focus on examples and case studies that are
Read more
Thinking of where our program might go wrong is never ending. However, there are situations where you can predict the most common types of errors and plan for their occurrence. In this post we will learn how to test for specific error exceptions in Python. Different types of errors As part of this series of tutorials (1, 2), we have
Read more
Scientifically Sound 