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NCRM Training: Quant for Qual Researchers
January 8, 2019 - January 10, 2019
As a rule, our courses cost £30 a day for UK/EU students and £60 a day for UK/EU academics, researchers or public service staff. Register for the event here.
|This course is aimed at researchers and teachers who have previously mostly worked in the qualitative tradition of research, but wish to understand or begin to research in the quantitative tradition. It assumes no more than a lay knowledge of quantitative methods (such as surveys or polling) and will take participants on a journey from the methodological and epistemological foundations of quantitative methods, through design, sampling and principles of analysis. No prior statistical knowledge is required and the course will mostly follow a problem based learning approach.
The course covers:
- The epistemological and methodological basis of quantitative methods and its challenges.
- Basic research design and quantitative – qualitative integration
- Introduction to sampling
- Introduction to questionnaire design and basic scaling
- Secondary analysis of existing data
- Introduction to basic analysis techniques and significance
By the end of the course participants will:
- Understand the reasoning underlying quantitative methods and their role in a pluralist approach to research
- Learn about basic design issues and how these inform methodological choices
- Be introduced to basic sampling decisions and techniques
- Learn how to go about designing a questionnaire and measure through simple scales
- Be aware of the possibilities of using existing data to answer research questions
- Learn about univariate and bivariate analysis
- Understand the concepts of central tendency and dispersion
- Learn how to use some simple descriptive statistics
Researchers or teachers of qualitative methods. The course caters for academics, or researchers in the government or third sector. It is open to all levels from early career researchers to experienced qualitative researchers.
Basic understanding of qualitative methods. Prior knowledge of SPSS is not required.