PSY4322 – Statistics for cognitive neuroscience

Knowledge

You will learn

• The principles and procedures of classical inferential statistics, the major statistical tests for single factors and multifactor designs.

• The principles and processes of Bayesian statistics, approaches to quantify model validity, and model comparisons.

• The principles of machine learning and their applicability to neuroscientific data • Appropriate sample size estimation for experimental designs.

• Principles of research plans and operationalization of research ideas.

• Preregistration of research plans.

Skills

• Be able to use statistical software packages to import, analyse, and report statistical results.

• Pre-process, clean, and prepare data for appropriate statistical testing.

• Compare statistical analysis procedures and quantify/qualify the appropriateness of statistical tests.

• Qualify the nature of experimental setups and experimental conditions, and prepare the correct statistical analysis pipeline.

• Choose appropriate parameter settings for statistical tests.

• Choose and apply documentation principles and formats for preregistration reports.

General competence

• Understands the concept of data quality and the complexity of neuroscientific data.

• Critically assess the scientific reasoning behind the choice of statistical methods.

• Competence in acquiring programming skills necessary for performing statistics within specific neuroscientific methods modalities (e.g. neuroimaging).

• Has the necessary theoretical and practical requirements to go on to preprocessing and analysing electrophysiological and neuroimaging data in the courses PSY4323 Electrophysiology in cognitive neuroscience and PSY4324 Neuroimaging in cognitive neuroscience.

Students who are admitted to study programmes at UiO must each semester register which courses and exams they wish to sign up for in Studentweb.

If you are not already enrolled as a student at UiO, please see our information about admission requirements and procedures.

The course is not available for singe course or exchange students.

The teaching is organized as workshops, each consisting of 2h lectures and 2h seminars with tutorials.