PhD Students and the Most Frequent Mistakes During Data Interpretation by Statistical Analysis Software
Correct choice and administration of a statistical test are absolutely essential for meaningful interpretation of research data, yet mistakes are still frequent and could be easily found in published scientific papers or PhD theses. The aim of this study was to analyze mistakes made by PhD students in statistical analysis of data collected during research within the framework of their thesis. PhD students frequently use Excel and SPSS for data processing, while SAS, Stata and R are also available. The study was designed as cross-sectional analysis of random sample (n=15) of PhD theses in pre-approval stage at Faculty of Medical Sciences, University of Kragujevac, Serbia. In total 14 (93%) theses had at least one mistake. The most frequent mistakes were as the following: insufficient statistical power due to small sample size, inappropriate presentation of results at tables and graphs, andinappropriate choice of statistical tests. In order to improve the situation, training courses in statistics during PhD studies should be re-evaluated and improved in regard to relevance, delivery methods and motivating potential, and mentors should invest more effort to review the data and guide students through statistical analysis.