Biostatistics, 6 credits

A Bachelor's degree or a professional degree worth at least 180 credits in biomedicine, biotechnology, cellular and molecular biology or medicine. English language skills equivalent to English B at Swedish upper secondary school.

The main aim of the course is to equip the participants with statistical concepts and tools for relating biological outcomes to multiple possible explanatory variables.

The course will mainly focus on regression modelling.
At the end of the course, students should be able to analyse a realistic data set by applying the appropriate regression model, identifying the role of different covariates, and using different methods to handle nonlinearity and interactions.
Upon completion of the course the student should be able to:

Regarding knowledge and understanding

• explain the concept of random variation in biological phenomena as it relates to experimental and observational studies in research,
• describe appropriate statistical methods to quantify random and systematic effects in complex biological data,
• discuss the distinction between explanatory and predictive modelling.

Regarding competence and skills

• choose and fit multivariate regression models of intermediate complexity using a standard statistical software package,
• communicate the results in a manner suitable for oral presentation, technical reporting and scientific publication,
• understand, discuss and evaluate critically corresponding findings of intermediate complexity in the relevant scientific literature.

Regarding judgement and approach

• demonstrate the ability to weigh and integrate conflicting empirical evidence in the literature.

Randomness of biological observations. Experimental and observational data. Types of data: nominal, ordinal, continuous variables. Data summary measures. Graphical representations. Concepts of probability and probability distributions. Parameter estimation: mean, proportion, standard deviation, standard error. Concepts of statistical inference: confidence intervals and hypothesis tests. Elementary parametric hypothesis tests. Univariate linear regression.

Multivariate linear regression and general linear model. Continuous and categorical predictors. Role of covariates. Interactions. Nonlinear effect of covariates. Model fitting and diagnostics. Generalised linear models and logistic regression. Survival analysis and Cox proportional hazard models.

Quantile regression. Models for longitudinal data.

Teaching will be in the form of lectures and practical computer activities.

The examination consists of written examination.  

Limitations of the number of examinations or practical training sessions
A student who does not pass the examination on the first occasion is offered a maximum of five additional opportunities to sit the examination. A student who fails the examination on six occasions is not permitted to sit the examination again or to retake the course.

Participation in an examination is defined as an occasion on which a student attends an examination, even if the student submits a blank examination paper. If a student has registered to sit an examination, but does not attend the examination, this is not defined as participation in the examination.

After each course occasion there will be at least six occasions for the examination within a 2-year period from the end of the course.

The course language is English.

Course evaluation will be carried out in accordance with the guidelines established by the Board of Higher Education.

Oral evaluation in the form of course council meetings will be carried out during the course.