Kies de Nederlandse taal
Course module: BMB507217
Basics of Biostatistics
Course info
Course codeBMB507217
Course goals
At the end of the course the student:
  1. has knowledge of the role that statistics plays in academic research;
  2. has knowledge of basic statistical techniques that are used to analyze data, and knows the conditions under which they are appropriate;
  3. has insight in which techniques are applicable in which situation;
  4. can apply these techniques by hand and by using statistical software (SPSS);
  5. is able to interpret the results from the statistical analysis;
  6. can report these results in the context of the research question.
Period (from – till):  13 November 2023 – 02 February 2024 (BMS_P2_A)

Introduction and discussion statistical theory: week 46 till week 51 2023 (online)
Christmas holiday: week 52 and 53 2023, week 1 2024
Case study (group assignment): week 2 2024 (online)
Exam (individual): week 3 2024 (UMC Utrecht)
Re-exam (individual): week 6 2024 (UMC Utrecht)
Paul Westers, GNK (coordinator and online instructor)
Cas Kruitwagen, GNK (web lecturers)
Rebecca Stellato, GNK (web lecturers)

Course description
Basic of Biostatistics is an online course. The course offers a variety of learning activities such as web lectures, discussions and (group)assignments.

The course (4,5 ECTS, study load 16 hours per week) provides the basics of statistical methodology and supplies a number of statistical techniques important for practical data analysis. Examples from the medical and biological fields will be used in exercises. Datasets will be analyzed on the computer using the statistical package SPSS or optional R.
The first part covers statistical testing for one and two samples, confidence intervals, simple linear regression and correlation, one way analysis of variance, binomial distribution and proportions, analysis of contingency tables and non-parametric statistics. The second part introduces the most important regression models used in biomedical research, that can be used in the study of the relation between a number of explanatory variables on the one hand, and the occurrence of an outcome on the other: multiple regression and logistic regression.

NOTE: It is expected that students have some basic knowledge on descriptive statistics and mathematics, such as measures of location (mean, median) and scale (variance, standard deviation), the normal distribution, standard error of the mean. They will not explicitly be repeated in the course, but will be used implicitly.

Literature/study material used:
During the course all the course material will be online available. Besides this online material you can use also one of the following statistical books:
  • W.W. Daniel, Biostatistics: Basic Concepts and Methodology for the Health Sciences, International student version, 9th Edition. John Wiley & Sons, 2010;
  • P. Armitage, G. Berry and J.N.S. Matthews, Statistical Methods in Medical Research, 4th edition. Wiley-Blackwell, 2001;
  • M.C. Whitlock and D. Schluter. The Analysis of Biological Data. Roberts and Company Publishers, 2009;
  • J.H. Zar, Biostatistical Analysis, 5th Edition. Pearson Education International, 2010.
These reference books remain useful long after you have completed the course. You are not obliged to use any of these books during the course.

Brief manuals of SPSS and R will be available online.

The examination consists of two parts, namely:
  1. a case study (in subgroups of 2-3 students, 25% of final grade)
  2. a final exam (individual, 75% of final grade) consisting of open and multiple choice questions.
The grades for both parts should be at least 5. To pass for the course the final grade should be at least 5.5. If the final grade is lower than 4 it is not allowed to do the re-exam, except if there is a permission from the exam committee.
Furthermore active (online) attendance is mandatory.

You can register for this course via Osiris Student. More information about the registration procedure can be found here on the Students' site.
A maximum of 60 students can be enrolled in the course (divided into groups of max 15 students in order to remain small-scale learning).

Mandatory for students in own Master’s programme:
Optional for students in other GSLS Master’s programme:

Prerequisite knowledge:
If necessary, participants should refresh their knowledge using a statistics book used in previous courses, or using the statistics e-books.

Although active statistical knowledge is not a prerequisite, we assume some basic knowledge on statistics and mathematics acquired through, for example, courses in biostatistics in the bachelor programme or self study.

The basic knowledge we assume are:
  • The concepts of population and sample;
  • Histogram, boxplot, frequency table, scatterplot, contingency table;
  • Mean, median, mode;
  • Variance, standard deviation, range, interquartile range, standard error of the mean;
  • Probability, probability distributions (especially the normal distribution).
If you want to refresh your basic knowledge, we recommend one of the mentioned books (see study material) or one of the following sources of information:
  • The very advanced online textbook Online Statbook;
  • The e-book and/or exercises of CAST (Computer-Assisted Statistics Textbooks)
  • The e-lectures and/or exercises of the Khan Academy (includes also a self-test)
  • The very nice JBstatistics with short video’s but no exercises (no descriptive statistics)
As soon as possible after the enrollment for the course you will get access to the online learning environment of the course and there will be a test available for testing your basic knowledge on statistics and mathematics. It is then also possible to ask online questions with respect to the basic knowledge to the lecturers.
Kies de Nederlandse taal