For students attending the course Biostatistics (4,5 hp) course code 1BI043

Information about the course

The content of the course can be roughly grouped into three parts:

Basics: these are elementary ideas and techniques on which all further statistics is based. This includes how to summarize and describe data numerically and graphically, the concept of probability and probability distributions, confidence intervals and hypothesis tests. These ideas are demonstrated for basic means and proportions.

Relationships: using the basic concepts, we will discuss how to measure and test relationships between two continous measurements (correlation and regression) as well as two nominal measurements (contingency tables).

Complementary: the standard parametric methods in 1. and 2. have some common assumptions that need to be fulfilled for the results to be valid. We will discuss formal and informal methods to help us decide whether these assumptions are valid (e.g. quantile plots) and introduce some alternative methods for dealing with situations where the assumptions do not hold (non-parametric tests). Besides being useful in their own right, these methods allow us to apply basic concepts (descriptive statistics, hypothesis testing)  from 1. in a slightly different context.

The course is strongly focused applying the statistical methods to realistic data. Consequently, ca. 40% of the classroom activity will be in form of exercises and computer labs.

Organization

The course starts September 2, 2024. Each day of instruction, we have scheduled lectures 9.00 - 12.00 and lab 13.00 - 16.00. 

Canvas

As a student you will get access to the course website in Canvas.

Examination

The examination is a written exam in Canvas. The exam is in program R and handed in as an R script in Canvas.

The exam is assessed as Fail, Pass or Pass with distinction.

Course material and software

Some course material will be available from the course web in Canvas.

You will mainly use the open-source statistical software R, which is freely available from the CRAN website. We will give a short introduction on using R with a simple graphical user interface during the first day. Feel free (actually, feel encouraged) to bring your own laptop (we will help you with installing R if you have problems).

Video demo of installation (8 min)

Literature

There is no dedicated course book: while there is no lack of excellent introductory biostatistics books, most are written for either clinical or public health researchers, and stress somewhat different aspects. Consequently, we try to put everything you need to pass the course into our handouts.

If you want to do some complementary reading (highly recommended!), the following books are well written, with excellent examples from biomedical research, and available from the KI Library:

DG Altman: Practical Medical Statistics

M Bland: An Introduction to Medical Statistics

M Pagano: Principles of Biostatistics

B Rosner: Fundamentals of Biostatistics (very detailed)

P Dalgaard: Introductory Statistics with R (software specific)

There is also a reasonable electronic book available via the KI Library:

S Mitchelson: The Biostatistics Cookbook

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