YRM-21806 Data Analysis for Health and Society

Course

Credits 6.00

Teaching methodContact hours
Lecture19
Tutorial24
Practical12
Independent study0
Course coordinator(s)dr. H Tobi
Lecturer(s)ir. SLGE Burgers
dr. EJH Korendijk
dr. H Tobi
dr. LMW Akkermans
Examiner(s)dr. H Tobi
dr. EJH Korendijk

Language of instruction:

Dutch.

Assumed knowledge on:

MAT-15303 Statistics 1, MAT-15403 Statistics 2, HNH-24806 Introduction to Epidemiology and Public Health, YRM-10306 Research Methods in the Social Sciences

Continuation courses:

YRM-50806 Quantitative Data Analysis: Multivariate Techniques, MAT-50806 Qualitative Data Analysis: Procedures and Strategies, YRM-30806: Research Methods and Data Analysis in Communication and Health

Registration:

The knowledge and skills that students acquire in this course are a must for anyone who deals with research in the health sciences and social sciences. The course is set up as a research practical where students collected and analyse data, report the results and critically discuss the data analytic approach used. Students will experience the complimentary nature of quantitative and qualitative data.

Contents:

Note: This course can not be combined in an individual programme with YRM 20806 Research Design and Research Methods and/or YSS 20306 Quantitative and Qualitative Research Techniques in the Social Sciences.;

Learning outcomes:

After successful completion of this course students are expected to be able to:
- explain some basic principles of 5 quantitative data-analysis techniques (cross-tabulation, analysis of variance, regression analysis, logistic regression and survival/time-to-event analysis) and 2 qualitative data analysis techniques (content analysis, metaphor analysis);
- select the appropriate data analysis technique given typical research questions and data;
- write a data analysis plan at BSc thesis level;
- apply the techniques introduced in this course and interpret the results produced;
- explain the complimentary nature of quantitative and qualitative data analysis;
- show a basic understanding of analyses presented in scientific papers and the ability to critically assess them;
- perform basic data processing operations and analysis in ATLAS.ti and SPSS.

Activities:

Plenary meetings consist of lectures on theory, workshops and computer practicals.

Examination:

- computer practicals are mandatory;
- written exam with multiple choice questions and open questions (90%);
- final group assignment (writing a data analysis plan) (10%);
To pass:
- the weighted average of exam and group assignment at least a 5.5 and
- at least a 6 on either the exam or group assignment and
- participation in all computer practicals.

Literature:

Andy Field. Discovering statistics using IBM SPSS statistics (5th edition, 2018).
For qualitative data analysis: to be announced.

ProgrammePhaseSpecializationPeriod
Compulsory for: BGMHealth and SocietyBSc6MO