practical, 1 semester hour
Content: introduction to the statistical software package SPSS, data entry, data management with SPSS, introduction to statistics, descriptive statistics: Basic measures and diagrams
Objective: successful completion will give PhD students a solid basic understanding of SPSS and statistics, which will be required for the advanced statistical courses (Medical biostatistics I and II)
Course notes will be provided in Moodle.
seminar, 2 semester hours
Requirement: basic knowledge of statistics and SPSS corresponding to SSM2 or Preparatory Course for Medical Biostatics; Students with a master degree in technical or formal science or in psychology are recommended to attend directly Medical Biostatistics II
Contents: descriptive statistics: introduction to SPSS, data entry, descriptive statistics and diagrams; Statistical tests: general principle of statistical testing, t-test, Wilcoxon, rank-sum/Mann-Whitney-U-test, chi-square-test, confidence intervals, multiple testing, analysis of variance, correlation, regression, sample size determination
Objective: understanding the use of standard statistical methods in medical publications and conducting own statistical analyses within research projects
Method: the courses are delivered in a seminar room equipped with computers on which the statistical software package SPSS is available. Each class begins with an introductory lecture. Directly after the lecture, students solve real-date problemes using computers.
Course notes will be provided in Moodle.
seminar, 2 semester hours
Requirement: statistical knowledge corresponding to Medical biostatistics I
Contents: statistical modelling; analysis of binary data: measures for diagnostic tests, ROC curves, risk estimates, logistic regression; analysis of survival data: censoring, Kaplan-Meier estimates, Cox regression, assessing model assumptions; analysis of repeated measurements: pretest-posttest data, display of repeated measurements, summary measures, repeated-measures ANOVA
Objective: understand the use of advanced statistical methods in medical publications, and conduct statistical analyses in own research projects
Method: lecture with exercises
Course notes will be provided in Moodle.