This online medical course, offered by the MSc Epidemiology program of the UMC Utrecht and Utrecht University, provides an understanding of the basic applications of biostatistics in the analysis of medical research data.
Topics are: types of data, location and variability measures, samples and populations, distributions, confidence intervals, hypothesis testing, comparing two or more means or proportions (parametric and non-parametric methods), and relationships between two variables (correlation, simple linear regression). The course also includes an extensive discussion of the multiple linear regression model. This is an ideal course for anyone who wishes to further his/her medical education by getting a better understanding of data analysis.
By the end of the course you will…
• have insight in the √n law and its consequences for sample size
• have insight in the general principles of decision procedures (“testing”), and be able to apply these procedures in practice using statistical package R
• understand the principles of the following statistical analysis techniques: Student T tests (1-sample, 2-sample and paired), Analysis of Variance (1-way and 2-way ANOVA), Simple and multiple linear regression analysis, 1-sample, 2-sample and paired proportion tests (χ 2 test for goodness-of-fit, Pearson’s χ 2 test and McNemar’s χ 2 test)
• know in which situations these techniques can be applied and the conditions that should be met to obtain reliable results using these techniques
• be able to apply these techniques using statistical package R
• understand the results obtained with these techniques, and be able to apply these results in practice (e.g. in answering a study questions
• be familiar with the terms ‘explained variance’ and multi-collinearity
• understand the principles of model reduction in regression analysis
• understand the basic principles of the technique of logistic regression analysis
• be able to choose the appropriate non-parametric technique to be applied in case of non-normally distributed data, and understand the principles of these methods.
Exam edition November 2023
The exam will take place on March 1st, 2024 at 14:15 CET. The re-examination will take place on April 19th, 2024 at 14:15 CET. Note: these times might be subject to change. The exact time and place will be announced as soon as possible in the learning environment and any changes announced there will overrule the information here.
Exam edition May 2024
The exam will take place on July 26th, 2024 at 14:15 CEST. The re-examination will take place on September 19th, 2024 from at 14:15 CEST. Note: these times might be subject to change. The exact time and place will be announced as soon as possible in the learning environment and any changes announced there will overrule the information here.
It might be that, due to a force majeure situation, you cannot be present during the first exam moment.
• MSc Epidemiology Postgraduate students must then, preferably prior to the first exam option, ask the academic counsellor for permission to be absent. Please note that the academic counsellor can ask for some form of proof of your absence (e.g. in case of illness) to establish if you are applicable for authorized absence. Jaco de Fockert-Koefoed, MSc is the academic counsellor you need to turn to through adviseurs@umcutrecht.nl.
• All other participants should contact the MSc Epidemiology Office instead, through MSc-Epidemiology@umcutrecht.nl.
In short, as of now, it is no longer possible to skip the first exam option and -automatically- enroll in the second (re-sit) exam. Unauthorized absence during the first exam period results in no longer being able to finish the course that college year.
To enroll in this course you need:
• A BSc degree
• To have participated in an introductory statistics course
• A sufficient proficiency in English reading and writing
• Access to the computer program R
Compulsory study materials
For this course, you will need:
• The Practice of Statistics in the Life Sciences” by Baldi and Moore (MacMillan publishers), 4th Edition
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