YRM-21806 Data Analysis for Health and Society

Course

Credits 6.00

Teaching methodContact hours
Lecture19
Tutorial24
Practical12
Independent study
Course coordinator(s)dr. H Tobi
Lecturer(s)dr. V Torres van Grinsven
dr. PA Tamas
dr. JV Meijering
dr. H Tobi
Examiner(s)dr. H Tobi

Language of instruction:

Dutch.

Assumed knowledge on:

MAT15303 Statistics 1, MAT15403 Statistics 2, HNE24806 Introduction to Epidemiology and Public Health, YRM10306 Research Methods in the Social Sciences

Continuation courses:

YRM30306 Research Methods in Public Health and Society, YRM60306 Quantitative Data Analysis: Multivariate Techniques, YRM60806 Qualitative Data Analysis: Procedures and Strategies

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.

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:

- written exam with multiple choice questions and open questions (60%);
- group assignment reports (based on computer practicals) (30%);
- final group assignment (writing a data analysis plan) (10%);
- to pass the overall average and the written exam require a 5.5.

Literature:

Field, Andy (2013). Discovering Statistics using IBM SPSS Statistics (4th ed.). Londen: Sage. Additional study materials to be announced.

ProgrammePhaseSpecializationPeriod
Compulsory for: BGMHealth and SocietyBSc6MO