Many relevant problems in medical science arise from the practical need for mathematical and statistical expertise in analyzing and interpreting data. A proper grounding in the fundamentals of statistics is essential for fellows to begin to formulate hypotheses, to design experiments to test them, and to properly interpret the findings. Too often, however, formal courses in statistics begin with extensive theoretical discussions without any practical application to real data.

The primary goal of this course is to teach statistical methods by describing clinical data that led to specific hypotheses and then discuss the different statistical tools needed to test these hypotheses. In this way, we stimulate the fellows' interest in and appreciation of statistical tools applied to disease-related research.

Course Description:

The series is divided into two parts.

During the first group of lectures, the fellows are introduced to specific statistical tools. These lectures are given by leading investigators in the field of clinical research. In addition, each lecturer teams with one of the fellows to discuss a specific paper using the technique. The fellow then leads a discussion of the paper for the other in the group.

The second series of lectures involves a team comprised of a clinical researcher and a statistician. Each lecture focuses on how particular statistical methods were applied to the analysis of a particular disease. In addition, important historical manuscripts related to medical statistics are used as examples of this integrated approach. Both adult and pediatric conditions are used as a springboard for quantitative analysis of biologic processes.

This practical course integrates basic science and clinical research methods from a bi-directional bench-to-bedside approach. Fellows will be equipped with tools and techniques needed to comprehend and critique research studies, with special emphasis on statistical tests and methods. The course also provides an intellectually broadening pedagogical experience by combining elements from many disciplines and introducing statistical concepts through real-life examples. ramifications.