Period (from – till):  11 November 2024 – 24 January 2025 (BMS_P2_A)

Schedule: 
Introduction and discussion statistical theory: week 46 till week 51 2024 (online)
Christmas holiday: week 52 2024, week 1 2025
Case study (group assignment): week 3 2025 (online)
Exam (individual): week 4 2025 (UMC Utrecht)
Re-exam (individual): week 8 2025 (UMC Utrecht)
 
Faculty
Marga Korporaal, GNK (coordinator and online instructor)
Cas Kruitwagen, GNK (web lecturers)
Rebecca Stellato, GNK (web lecturers)

Course description
This ten week course (4.5 ECTS, 16 hours per week) provides an introduction to statistical methodology. A number of statistical techniques are covered that are relevant for practical biomedical data analysis.

This course covers the concepts of statistical estimation (point and interval estimation) and testing. It focuses on methods developed for categorical data, in particular binary data, and quantitative data, in particular normally distributed data. The course covers, simple linear regression, correlation, one way analysis of variance, analysis of contingency tables and non-parametric statistics. Furthermore, it introduces (multiple) linear regression and (multiple) logistic regression.

The theory will be presented during web lectures and you will have the opportunity to practice your skills through exercises, discussions, quizzes, assignments and case studies of realistic and real data.

Literature/study material used:
During the course all the transparencies of the web lectures and the exercises (with answers) of the learning units will be online available. Besides this course material you can use also one of the following statistical books:

1. B. Baldi and D.S. Moore, The Practice of Statistics in the Life Sciences, stat 4^th Edition. W.H. Freeman and Company, 2014.
2. W.W. Daniel, Biostatistics: Basic Concepts and Methodology for the Health Sciences, International student version, 9^th Edition. John Wiley & Sons, 2010.
3. P. Armitage, G. Berry and J.N.S. Matthews, Statistical Methods in Medical Research, 4^th Edition. Wiley-Blackwell, 2001.
4. M.C. Whitlock and D. Schluter. The Analysis of Biological Data, 2^nd Edition. Roberts and Company Publishers, 2015.
5. J.H. Zar, Biostatistical Analysis, 5^th Edition. Pearson Education International, 2010.

The first two books have more medical examples, whereas the next two books more biological. The last book has more life sciences examples, but in contrast with the other books discusses less statistical methods.

These reference books remain useful long after you have completed the course. They can be obtained from scientific bookstores. You are not obliged to use any of these books during the course.

Examination
The examination consists of two parts, namely:

1. a case study (25% of final grade)
2. a final exam  (75% of final grade)

The exam consists of a combination of open and closed (multiple-choice or fill-in) questions.

The grade for the final test and the case study must both be at least 5 and the final grade at least a 5.5 to pass for the course. Furthermore, active attendance is mandatory.

Registration
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:
N.A.
 
Optional for students in other GSLS Master’s programme:
Yes.

Prerequisite knowledge:
Although active statistical knowledge is not a prerequisite, we expect some basic knowledge of statistics and mathematics acquired through, for example, courses in biostatistics in the bachelor program or self-study.

It is assumed that you

• are familiar with the concepts of a “population” versus a “sample”
• can interpret data presented in the form of a histogram, boxplot, frequency table, scatterplot or contingency table
• can calculate and interpret from a sequence of numbers: the mean, median, variance, standard deviation, range, interquartile range, standard error of the mean
• are familiar with the concepts probability and probability distributions (in particular the standard normal distribution).

If you want to refresh your basic knowledge we recommend one of the following sources of information (see also literature/study material):

1. Chapters 1 - 5 of the book of W.W. Daniel
2. Chapters 1 - 3 of the book of P. Armitage, G. Berry and J.N.S. Matthews
3. Chapters 1, 2, 3, 5 and 10 of the book by M.C. Whitlock and D. Schluter
4. Chapters 1 - 6 of the book of J.H. Zar
5. Chapters 1, 2, 3 (first 3 paragraphs), 11, 13 of the book of B. Baldi and D.S. Moore
6. Module I, II, III, V of the very advanced online textbook Online Statbook
7. Modules 1 and 2 (e-book) and/or module 1 (exercises) of CAST (Computer-Assisted Statistics Textbooks) that consists of a collection of electronic textbooks (e-books). Under “Core e-books”, choose the “Introductory statistics e-book (biometrics)”, chapters 1 and 2 and section 3.1. These can be downloaded from the CAST website for free.
8. Chapters 1 – 4 of Field, Discovering Statistics Using SPSS, 5th edition. SAGE Publications Ltd, 2017. Chapter 3 provides some early insights in the workings of (the statistical program) SPSS. SPSS will be used during the course.

In LU-0 there will be a test available for testing your basic knowledge on statistics and mathematics. It is then also possible to ask questions with respect to the basic knowledge to the lecturers.