This course is part of the Neurosciences master program at the VU.
It counts in the category "Courses on other subjects".
Statistical data analysis is the process of inspecting, cleaning, transforming, and modelling data in order to test scientific hypotheses and answer research questions. Each lecture will provide the theoretical background. The practicals and weekly obligatory assignments will guide students through a series of tailored research problems that they will tackle using the statistical package R. Students will receive hands-on experience in the main steps involved in statistical analyses: from the formulation of hypotheses, selection of the most appropriate test, checking of assumptions, cleaning of data, and running of analyses in R, to formally reporting the obtained results.
The lectures of this course will provide an overview of quantitative methods that are frequently used in neuroscience research. These include:
REQUIRED BACKGROUND LEVEL
Students are assumed to be familiar with chapters 1-5, 7, and 9 of the book "Discovering statistics using R" by Field, Miles & Field before entering the course. The first lectures, practicals, and assignments will provide a short review of these chapters. A short diagnostic entry test will be provided to give students insight into their knowledge of statistics at the start of the course.
Lectures, computer practicals, weekly assignments, written exam. The weekly assignments are pass/fail: you need to pass all assignments before you can participate in the exam.
168 hrs / 6 ECTs
Please note that the course will take you about 20 hours/week, a.o. due to the practicals, assignments, etc., you are expected to participate in all parts.
Dr. Sophie van der Sluis (VUmc)
Tuesdays in September - October 2022
To register, please send an e-mail to firstname.lastname@example.org