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Responsible Data Analysis


Admission requirements

Study Design


Brief introductory description of the course (max 250 words). Please include course subject and teaching materials used.

In most areas of health, data is being used to make important decisions. As a health population manager, you will have the opportunity to use data to answer interesting questions. In this course, we will discuss data analysis from a responsible perspective, which will help you to extract useful information from data and enlarge your knowledge about specific aspects of interest of the population. First, you will learn how to obtain, safely gather, clean and explore data. Then, we will discuss that because data are usually obtained from a sample of a limited number of individuals, statistical methods are needed to make claims about the whole population of interest. You will discover how statistical inference, hypothesis testing and regression techniques will help you to make the connection between samples and populations. A final important aspect is interpreting and reporting. How can we transform information into knowledge? How can we separate trustworthy information from noise? In the last part of the course, we will cover the critical assessment of the results, and we will discuss challenges and dangers of data analysis in the era of big data and massive amounts of information. In this course, we will emphasize the concepts introduced through video-lectures, further addressed in reading activities and individual home assigments and intensively discussed on group assigments. We will also teach you how to effectively perform your analysis using R through interactive tutorials and live sessions.

Course objectives

Concise description of the course objectives formulated in terms of knowledge, insight and skills students will have acquired at the end of the course. The relationship between these objectives and achievement levels for the programme should be evident. (max 150 words)
Upon successful completion of this course, you should be able to:

  • Explain how to obtain, store, clean and explore the data necessary to answer a research question.

  • Design data collection protocols and perform initial data analysis.

  • Recall basic and modern statistical concepts (like estimation, testing and regression) and recognize them as a collection of tools to analyze complex data.

  • Apply different types of statistical techniques, interpret and report the results given the characteristics of the data and study design.

  • Choose the appropriate data analysis methods in common population health management research situations.

  • Recognise the challenges and dangers of data analysis in the era of big data and massive amounts of information.

  • Critically assess data analysis results in the context of population health management.

  • Effectivelly communicate data analysis results and formulate recommendations in the context of population health management.


The timetable is published on the LUMC roostersite or can be found via the LUMC scheduling app.

Mode of instruction

  • Lecture

  • online education

  • group work

Assessment method

Students are assessed according to the following three obligatory components

Week 1-2 – Online:
20% Peer review assessment

Week 3 – On Campus:
30% Group presentation

Week 4 – Final week:
50% Final assignment
All components together make up the grade for the course. It is compulsory to participate in each of the components in order to receive a grade
Details on the assessment can be found in the assessment plan on Brightspace
A minimum result of 5,5 for the overall assessment is required to pass.
If the result is less than 5,5 or if the student didn’t participate in one of the components, the student is given the opportunity to resit the assessment as one assignment that covers all the learning goals of the course.

A final grade of 5,5 minimum is considered sufficient.

Reading list

The reading list can be found on Brigthspace. These are given as presentations and pdf files. There is no need to purchase literature, as the presented material is not commercialized.


Registration must be done via uSis at the latest 5 days before the start of the course. Registration in uSis gives you automatic access to the course in Brightspace.


Contact information

Mar Rodríguez-Girondo, PhD


This course is a combination of online ecucation and on campus Education at Leiden University Campus The Hague.