Data and Measurement Flashcards
Describe Large C QUANTITATIVE RESEARCH data sets. How do they express data, what sort of data do they use, what form of indicators do they use? What degree of standardising do they display?
Large C QUANTITATIVE data sets express their data as numbers. They use quantitative data, using forms of indicators such as numbers and statistics. They have high degrees of standardisation.
Describe Small C SCIENTIFIC REALISM data sets. How do they express data, what sort of data do they use, what form of indicators do they use? What degree of standardising do they display?
Small C SCIENTIFIC REALISM data sets express their data as numbers and as meanings. They use qualitative and quantitative data, using forms of indicators such as numbers, statistics, processes, words and symbols. They have high or average degrees of standardisation.
Describe Small C INTERPRETIVIST data sets. How do they express data, what sort of data do they use, what form of indicators do they use? What degree of standardising do they display?
Small C INTERPRETIVIST data sets express their data as meanings. They use qualitative data, using forms of indicators such as words and symbols. They have low degrees of standardisation.
What are nominal measurement levels? How do these categorise data and what examples are there of these?
Nominal measurement levels classifies data in a way without a natural order/ranking. This can be types of political system or party affiliations.
What are ordinal measurement levels? How do these categorise data and what examples are there of these?
Ordinal measurement levels arrange data in a meaningful order, but with asymmetric intervals between rankings. This can include levels of interest in politics (not interested to very interested), education levels, etc.
What are interval measurement levels? How do these categorise data and what examples are there of these?
Interval measurement levels are scales with equal intervals between values BUT without a true zero point. Zero rating has a value ascribed, not merely meaning nothing. Examples include ranking of ideology from 0-10 on a liberal-conservative scale.
What are ratio measurement levels? How do these categorise data and what examples are there of these?
Ratio measurement levels are numeric scales with equal intervals AND a meaningful zero point, where a value of 0 means nothing of that variable. This can include govt spending in GBP, number of protests attended, etc.
Explain the process of operationalisation
Operationalisation begins with a concept and a definition of this. This concept then has specific observable indicators that are identified as a proxy for that concept, before stating how this will be measured and then measuring this concept to fully OPERATIONALISE IT!
What is the difference between a unit of analysis and a unit of measurement?
Unit of analysis = WHERE are you looking to analyse?
Unit of measurement = what is the smallest level of data that is analysed to measure a variable
What criteria must an operationalised concept meet in order to be a good measure of a concept?
Indicators identified to measure a concept must be RELEVANT to the concept, they must cover the RANGE of the concept, does it PREDICT a particular outcome, does it identify with other measures?
What indicates that an operationalised concept is reliable?
It is unified across cases, it is agreed upon across different sources, and can be repeated with the same unit of analysis to reach similar conclusions.
Describe the collection process for primary data
Primary data is collected DIRECTLY by the researcher. They have full control over the data gathering process, which is often expensive and difficult to conduct.
Describe the collection process for secondary data
Secondary data is data gathered by other sources and then used by a researcher. They have less control over a research process, but it is less expensive and quicker.
Provide examples of Large C data and sources
Survey results, parliamentary votes, coding of policy positions from parties and manifestos, govt statistics, etc.
Provide examples of Small C, interpretivist data and sources
Coded transcripts from long form interviews, participant observation notes, coded party manifestos, academic articles, etc.
