Statistics in biomedical research III

Summary

The article deals with common mistakes in data presentation, interpretation and publication. It points out the most frequent mistakes in graphic data presentation. It explains the relations between causality and correlation. It reminds of the necessity of thinking about a possible coincidence or confounding factors. It deals with the misunderstanding and misinterpretation of the p-value. It mentions publication bias which occurs when authors and editors publish mostly positive findings. It recommends researchers to contact a statistician before commencing a study.

Keywords:
data presentation – data interpretation – p-value interpretation – data publication – publication bias