Background. We changed the biostatistics curriculum for our medical students and have created a course entitled “Multivariate analysis of statistical data, using the SPSS package.” Purposes. The aim of this course was to develop students’ skills in computerized data analysis, as well as enhancing their ability to read and interpret statistical data analysis in the literature. Methods. In the current study we have shown that a computer-based course for biostatistics and advanced data analysis is feasible and efficient, using course specific evaluation questionnaires. Results. Its efficacy is both subjective (our subjects felt better prepared to do their theses, as well as to read articles with advanced statistical data analysis) and objective (their knowledge of how and when to apply statistical procedures seemed to improve). Conclusions. We showed that a formal evaluative process for such a course is possible and that it enhances the learning experience both for the students and their teachers. In the current study we have shown that a computer-based course for biostatistics and advanced data analysis is feasible and efficient. 1. Introduction Physicians need to use and interpret statistical and epidemiological data on a daily basis. Colditz and Emerson [1] found that more than 40% of 700 medical articles they reviewed utilized advanced statistical procedures, like regression MANOVA and the like. Paltiel et al. [2] believe that today’s medical decision-making requires enhanced capabilities in communication as well as data analysis. To develop these skills and those necessary to conduct and interpret clinical research, medical students would benefit from training in evidence based medicine (EBM), epidemiology, and biostatistics. That is why the field of biostatistics has become an integral part of the medical milieu [3]. Studies have shown that physicians have a difficult time grasping statistical logic, understanding its importance relative to the treatment of patients, and conducting their own research [3]. Sterne [4] believes that the problematic issue of statistical inference, as well as how to teach it, is as old as statistics itself. The tendency of medical literature today to ask for unneeded and problematic statistical procedures is an outcome of the variability of teaching methods of these subjects. Sterne calls for the implementation of guidelines to standardize what should be taught to medical students. Medical students themselves [5, 6] understand the need to learn statistics, especially as an essential language to understand the medical
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