Introduction to Biostatistical Computing

Lecturer Arthur Allignol
Exercises taught by Maria Umlauft


General Informations

Language English

Lectures   2h
Exercises 1h

The exercise sheets are on the SLC

Prerequisites: The level of the course is that of a last year's bachelor course in Mathematical Biometry. Some basic programming knowledge 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.


Time and Venue 

Lectures Thursday, 14:00-16:00, HeHo 18, E44

Exercises Thursday, 11:00-12:00, N24/254

16.4 no exercise


Exam

tba


Contents

Computing and programming is an essential part of a statistician's work. The goal of this course is first to acquire good programming habits,i.e, learn to write maintenable code, test code for correctness and be able to follow the precepts of Reproducible Research (literate programming). The second aim is to prepare students to deal with real life, i.e., complex and dirty, data sets. Finally, how to conduct a simulation study in order to, e.g., study the small sample properties of a new statistical method, will be presented.

The first part of the course will be taught with R and SAS programming languages, the rest with R.


Literature:

Christopher Gandru, Reproducible Research with R and RStudio, CRC Press, 2013