Biostatistical methods

Lecturer: Jan Beyersmann

Exercises: Jan Feifel

General Information

Language

English, unless all students have sufficient knowledge of German
Lectures2 h
Exercises1 h

Lectures Thursday 2:00 p.m. - 4:00 p.m. (H12)

Exercise Friday 12:00 p.m. -2:00 p.m. HeHo 18 R.120

Every two weeks, starting at 28.10.2016


Exam (open)

16.02.2017 (oral)
 

General Informations:

Prerequisites:

Elementary Probability Calculus, Stochastik I and Measure Theory. The level of the course is that of a first year's masters course in Mathematical Biometry, but students of Mathematics or Business Mathematics are welcome, too. Some basic programming knowledge in R would be helpful.

 

Exam:In order to be admitted to the exam, students must have made a meaningful attempt to solve at least 80% of all Problems.

Contents:

The lecture covers some common biostatistical ground, which every student in Mathematical Biometry should know. Students of Mathematics and Business Mathematics contemplating a career in the life sciences will also find this lecture helpful. We will start with basic biometric measures of risk, studying both their interpretation and their mathematical properties. Next, we'll consider the related questions of study planning and research synthesis - two important fields in any biometrician's practical work - before moving on to stratified and matched analyses. In the last third of the lecture, we'll turn to the rather fundamental question of "Why statistics?", discussing prediction (which is not the same thing as significance) and causality. In particular, these last two topics will touch upon current research areas (not just) in biostatistics. We will, however, defer the (mathematically more challenging) biometric key discipline Survival and Event History Analysis to the summer term. (Although causality will require some discussion of time.)


Exercise Sheets

on Moodle.



 

 Literature: 

Link to Semesterapparat

Notes