About the lecture

In this lecture, we think about quantitative and qualitative methods, focusing in particular on: (i) defining research methods as the strategies used in the collection of information to generate understanding of a phenomenon; (ii) the subclasses of research methods being data sampling, collection and analysis; (iii) defining primary research as that which is conducted by the researcher themselves; (iv) defining secondary research as that which is done on an existing dataset; (v) differentiating between probability based and non-probability based sampling methods, the former including simple random sampling and systematic sampling and the latter including convenience sampling and snowball sampling; (vi) quantitative and qualitative data collection methods, the former including surveys and experiments and the latter including interviews and ethnography; (vii) defining a survey as a series of questions which’s answers can be quantified and used to make inferences about the population of respondents; (viii) some key parameters required to ensure good survey-based research; (ix) differentiating between cross-sectional and longitudinal surveys; (x) defining an experiment as a data collection procedure used to verify or reject a hypothesis; (xi) the necessity of participant condition random allocation in an experiment and differentiating between the experimental and control conditions; (xii) the two main types of interview, as qualitative methods, being individual interviews and focus groups; (xiii) an interview schedule, which can be structured, semi-structured or unstructured, which guides the interview or focus group; (xiv) defining ethnography as the observation and data collection of people in naturally occurring environments and situations; (xv) participant observation, field notes and unstructured interviews as examples of ethnographic methods; (xvi) thematic analysis as a data analysis technique, under which many others exist as derivatives; (xvii) dividing quantitative data analysis techniques into descriptive statistics and inferential statistics; (xviii) understanding statistical significance to mean the likelihood that the results which have been found are due to chance; (xix) p-values as a method of reporting the extent of statistical significance in a relationship between variables; (xx) mixed methods being the use of several research methods in data collection or analysis, to improve the validity and reliability of results; (xxi) an overview of in which situation it is best to use which data collection method; (xxii) defining triangulation as confirming validity and reliability of data by relying on multiple sources; (xxiii) a few examples of research questions, posed with a suggestion of which data collection method would be best used to answer it.

About the lecturer

Dr Rodolfo Leyva is a lecturer in quantitative methods in the Department of Social Policy, Sociology and Criminology at the University of Birmingham. Dr Leyva’s research interests are in experimental social science, direct democracy and civil disobedience. Some of Dr Leyva’s recent publications include ‘Media Ethics, Regulations, And Effects: How The British Right-Wing Press Disregards All Three & Undermines Democratic Deliberations’ (2020) and ‘Testing & Unpacking The Effects Of Digital Fake News On Presidential Candidate Evaluations & Voter Support.’ (2020).