Overview
What can you do with QCA?
- QCA is a comparative method that is mainly used in the social sciences for the assessment of cause-effect relations (i.e. causation).
- QCA is relevant for researchers who normally work with qualitative methods and are looking for a more systematic way of comparing and assessing cases.
- QCA is also useful for quantitative researchers who like to assess alternative (more complex) aspects of causation, such as how factors work together in producing an effect.
- QCA can be used for the analysis of cases on all levels: macro (e.g. countries), meso (e.g. organizations) and micro (e.g. individuals).
- QCA is mostly used for research of small- and medium-sized samples and populations (10-100 cases), but it can also be used for larger groups. Ideally, the number of cases is at least 10. QCA cannot be used if you are doing an in-depth study of one case.
What will you learn in this course?
After the course you will understand the methodological foundations of QCA.
After the course you will know how to conduct a basic QCA study by yourself.
How is this course organized?
- The MOOC takes five weeks. The specific learning objectives and activities per week are mentioned in appendix A of the course guide. Please find the course guide under Resources in the main menu.
- The learning objectives with regard to understanding the foundations of QCA and practically conducting a QCA study are pursued throughout the course. However, week 1 focuses more on the general analytic foundations, and weeks 2 to 5 are more about the practical aspects of a QCA study.
- The activities of the Qualitative Comparative Analysis (QCA) course offered by Coursera in partnership with Erasmus University Rotterdam include watching the videos, consulting supplementary material where necessary, and doing assignments. The activities should be done in that order: first watch the videos; then consult supplementary material (if desired) for more details and examples; then do the assignments.
- There are 10 assignments. Appendix A in the course guide states the estimated time needed to make the assignments and how the assignments are graded. Only assignments 1 to 6 and 8 are mandatory. These 7 mandatory assignments must be completed successfully to pass the course.
- Making the assignments successfully is one condition for receiving a course certificate.
Programme Structure
Courses include:
- Qca Vs Other Approaches
- Set Theory And Complex Causality
- Crisp Vs Fuzzy Sets
- Calibration With Quantitative, Qualitative And Secondary Data
- Raw Consistency
- Raw Consistency
Key information
Duration
- Part-time
- 21 days
- 10 hrs/week
Start dates & application deadlines
Language
Delivered
- Self-paced
Campus Location
- Mountain View, United States
Disciplines
Data Analytics View 179 other Short Courses in Data Analytics in United StatesWhat students do after studying
Academic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
We are not aware of any English requirements for this programme.
Other requirements
General requirements
- Beginner Level
- This course is aimed at learners interested in research methods, particularly those in the social sciences, who want to systematically analyze cause‑effect relationships using qualitative comparative analysis (QCA).
Tuition Fees
-
International Applies to you
Applies to youNon-residentsFree - Out-of-StateFree
-
Domestic
Applies to youIn-StateFree
Additional Details
- This short course is included with Coursera Plus subscription
Funding
Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You’ll be prompted to complete an application and will be notified if you are approved.