|Course coordinator(s)||dr. EJH Korendijk|
|Lecturer(s)||dr. LMW Akkermans|
|dr. EJH Korendijk|
|dr. AJ Boevé|
|dr. H Tobi|
|Examiner(s)||dr. EJH Korendijk|
|dr. H Tobi|
Language of instruction:
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
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
Note: This course can not be combined in an individual programme with YSS 20306 Quantitative and Qualitative Research Techniques in the Social Sciences.
This course provides an introduction to 5 methods for the analysis of quantitative data (cross-tabulation, analysis of variance, regression analysis, logistic regression and survival/time-to-event analysis) and 2 methods for the analysis of qualitative data analysis (content analysis and metaphor analysis) that are essential in the study of health and society. Also, the complementary value of mixed methods research is discussed. The course is set up as follows: in lectures the methods are introduced, in workshops and computer practical using SPSS and Atlas.ti these methods are practiced.In yet another workshop, student practice in critically assessing scientific papers in the field of health and society that made use of the data analysis methods.
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.
Plenary meetings consist of lectures on theory, workshops and computer practicals.
- computer practicals are mandatory;
- written exam with multiple choice questions and open questions (90%);
- final group assignment (writing a data analysis plan) (10%);
- 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.
Andy Field. Discovering statistics using IBM SPSS statistics (5th edition, 2018).
For qualitative data analysis: to be announced.
|Verplicht voor:||BGM||Health and Society||BSc||6MO|