Course Objective

The aim of the course is to introduce several standard statistical
methods and the use of the statistical software SPSS to the students.

Course Content

This course focuses on the practical application and interpretation of
statistical analyses. A lot of attention is given to regression analysis
in case of continuous, binary or survival outcome variables. But also
the t-test, the chi-square test and analysis of variance are discussed.
• analysis of continuous outcome variables: t-test, ANOVA and linear
• analysis of binary outcome variables: chi-square test and logistic
• analysis of survival data: Kaplan Meier curves and Cox regression
• multiple regression analysis: association and prediction models;
• repeated measures analysis: repeated measures ANOVA.

Teaching Methods

The course consists of seven lectures, seven exercise classes and
self-study. In the exercise classes students will actively apply the
discussed methods to several datasets using the statistical software

Method of Assessment

Final examination will take place via a written (open book) exam (50%)
and an SPSS assignment (50%). Grades of both the written exam and the
SPSS assignment have to be ≥ 5.5 in order to pass the course

Study load
7 lectures (3 hours each): 21 hours
7 SPSS practical s(4 hours): 28 hours
theoretical exam: 02 hours
SPSS assignment: 08 hours
self-study: 25 hours
Total 84 hours (3 ECTS x 28 hours)


Course reading – advised, not compulsory
1. BR Kirkwood & JAC Sterne (2003). Essential Medical Statistics - 2nd
Blackwell Science Ltd, Oxford
2. Gerber, SB and Voelkl Finn, K (2005). Using SPSS for Windows – data
analysis and
graphics. Springer, New York (electronic access at university via

Target Audience

The course is compulsory for of the Master Oncology program.
External candidates are also allowed, if accepted by the program
coordinator. Students from other master programs must have basic
knowledge of Oncology and Immunology and will only be accepted when the
number of master Oncology students is less than 40. They have to send
their cv, motivation and transcript of records via email to the program
coordinator. At the beginning of July 2019, students will be informed
about the acceptance.

Additional Information

Examinator: Tim van de Brug
Vakcoördinator: Tim van de Brug

Custom Course Registration

All students of the Master Oncology program have to attend the compulsory courses. For all you courses you must register through This way, you find out immediately if a place is available. All activities for which you are registered will be displayed in your personal timetable, which also includes any timetable changes. If you have not registered for a course then you will not be admitted to that course, you will not be assigned to a group, you will not be able to use CANVAS, you will have no timetable, your grades will not be recorded, etc. In short, you will not be able to take part. From the moment that you are conditionally registered for a program, you can sign up for specific courses via VUnet.

Recommended background knowledge

Some basic knowledge on (descriptive) statistics is recommended:
different types of variables [binary, categorical and continuous],
different ways to describe data [mean, standard deviation, median, inter
quartile range, proportion] and to report data [frequency tables,
scatterplot, histogram, boxplot].

General Information

Course Code M_FBIOSTA16
Credits 3 EC
Period P3
Course Level 500
Language of Tuition English
Faculty VUmc School of Medical Sciences
Course Coordinator dr. T. van de Brug
Examiner dr. T. van de Brug
Teaching Staff

Practical Information

You need to register for this course yourself

Teaching Methods Lecture, Practical