Within the biomedical sciences in Germany there is a striking discrepancy between internationally competitive basic research and poorly developed patient-oriented and clinical research. Thus, there is a critical need for postgraduate programs that train young medical and natural science graduates in basic and translational research to enable them to become future leaders in the fields of biomedicine and translational research, in academia, the public sector, as well as in the pharmaceutical industry.
The Mainz Research School of Translational Biomedicine (TransMed) addresses this need by providing an integrated, multidisciplinary training curriculum in all aspects of translational medicine.
TransMed is jointly run by four Faculties of the Johannes Gutenberg University Mainz: University Medical Center, Biology, Chemistry/Pharmaceutical Sciences/Geosciences, and Social Sciences/Media/Sports. TransMed plays a multifaceted role. It serves as the graduate school of the Research Center "Translational Medicine" with its three research areas "Immunotherapy", "Translational Neurosciences", and "Translational Vascular Biology". Beyond this, TransMed is the umbrella organization for all training groups within the area of biomedicine at JGU:
TransMed offers unique features for both clinician scientists and natural scientists. More information can be found in the TransMed Image Movie. Please also check the TransMed Curriculum and the Training Program offered.
“Unfortunately, too many people like to do their statistical work as they say their prayers – merely substitute in a formula found in a highly respected book written a long time ago” (Hotelling et al., Annals of Mathematical Statistics 19:95).Although this statement is now 60 years old, it still holds true. The teaching goal of this course, therefore, is to provide a deeper understanding of statistical methods, which can only be achieved by teaching students some of the basics of probability theory.We will start out with descriptive statistics, including correlation, regression, and effect size measures. Touching upon probability theory, we will then delve into the realms of inferential statistics. Rather than covering two dozen different hypothesis tests , we will exploit the fact that all these tests follow a common logic ("null-hypothesis significance testing (NHST)"). This logic can best be outlined using the binomial test, which is the test most amenable to students with limited knowledge of probability theory. Building on this foundation, we explain the usage and pitfalls of some of the most common forms of NHST (z-test, t-test, analysis of variance, chi square test, nonparametric tests), with a special emphasis on statistical power. In addition, we encourage students to approach their data with an exploratory attitude as outlined in Tukey’s seminal work on Exploratory Data Analysis. This is important because hypothesis tests yield highly processed data (p-values) that are prone to misinterpretation.
Students are expected to bring their own laptops running copies of either Microsoft Excel or Open Office Calc, which will be used for some exercises.
|Date||Monday 26. February 2018|
|bis Friday 2. March 2018|
|Time||09:00 - 17:00 Uhr|
Seminar Room 5 (01-355), Vorklinisches Lehrzentrum (VLZ), J.-J.-Becherweg 13 (Campus)
Jun.-Prof. Dr. Maik C. Stüttgen & Jun.-Prof. Dr. Albrecht Stroh
|Education Credits||5 CP TransMed|
Jun.-Prof. Dr. Maik C. Stüttgen