C2 Flashcards
how can research be classified?
Nature of research enquiry - exploratory, descriptive, explanatory or causal
Status or source of data - primary / secondary
Type of data - qual / quant
Mode of data collection - ad hoc, continuous
Method of data collection - observation / interview; personal / self-completion; F2F / telephone / online / postal
Type of research design - cross sectional, longitudinal, explanatory or causal, experimental, case study
exploratory research?
undertaken to explore issues or topics. Particularly useful in identifying a problem, clarifying nature of problem or defining issues involved. Can be used to develop propositions & hypotheses for further research
Descriptive?
to answer more clearly defined research questions, aims to build a picture e.g. who is buying brand B / how many people were a victim of hate crime this year. Aims to identify, describe and in some cases quantify things
Causal / explanatory research?
addresses ‘why’ questions, often conclusive e.g. why did people choose brand A over B, why do some prisoners and not others use drugs? These questions allow us to rule out rival explanations and come to a conclusion, to help us develop causal explanations.
Causal explanations
seeks to discover whether one thing (varaible Y) is affected by another thing (variable B)
Covariance and correlation ?
In order to see whether there is a relationship between two variables, you can examine cross tabs of one variable against the other, or plot graphs of one variable against the other by using covariance and correlation statistical techniques.
There may be a direct causal relationship - the change in Y is directly caused by X (e.g. sales and ad spend). But there may be an indirect causal relationship, in the link between Y and X there may be an intervening variable - if you want to rule out possibility that there is another variable involved the research design must allow you to examine its effect.
Important to remember that two things may co-vary, where a change in Y is accompanied by a change in X, and may be due to an extraneous / confounding variable - research should be designed in such a way that you can determine what sort of relationship there is and what is involved.
Inferring causation
You can see covariance, association and correlation but you cannot see causation - it must be inferred. In order to do this you must ensure that research design allows you to do the following:
Look for presence of association, covariance or correlation
If there is a casual relationship between Y & X then it should be expected to see an association between them - a change in Y associated with a change in X. in assessing the evidence for cause you should take into accoun the degree of association between X and Y - you may make one inference on the basis of a strong correlation but a different one on a weak one.
Look for an appropriate time sequence
The effect must follow the cause, thus if X causes Y - X has to precede the effect on Y
Rule out other variables a the cause
A third variable may be the cause of the perceived impact that X has on Y. the ability to rule out other variables rests to some extent on your ability o identify which other variables may be involved.
Come to plausible or common-sense conclusions
Likelihood of explanations, possibility that X may have impacted Y, what other evidence points towards
Primary research
Designed to generate or collect data for a specific problem - data collected does not exist prior to data collection. Can be exploratory, descriptive / causal; qual / quant; syndicated or customised
Secondary research
Process of 2ndry research involves identifying suitable sources, finding sources and gaining access, reviewing them and assessing suitability for your research objectives and evaluating their quality; learning from them; using / assimilating them into own research / thinking about own research or using them to address research objectives.
Secondary research sources
Documents - journal articles and research reports, books
External data - government produced statistics
Data generated by organisation - sales data, data from previous research projects
Quant rsearch?
Involves collecting data from relatively large samples and are typically presented as numbers, often in tables, on graphs and on charts. It provides nomothetic description - general / universal descriptions on a typically large number of case.
Can be collected via census, sample surveys or panels.
Nomothetic?
provides nomothetic description - general / universal descriptions on a typically large number of cases. Qual on the other hand provides idiographic description, that is, description that is rich in detail but limited to few cases.
Idiographic?
It provides nomothetic description - general / universal descriptions on a typically large number of cases. Qual on the other hand provides idiographic description, that is, description that is rich in detail but limited to few cases.
Quant interviews and how they differ to qual?
Quant interviews are structured and standardised - worded exactly the same way and asked in the same order in each interview. Where qual interviews are more like conversations on a spectrum of semi-structured and semi-standardised to unstructured and non-standardised.
Quant interviews can be conducted F2F (in street, central venue, ‘hall test’ / central location test, respondents home or place of work), telephone, post, online.
Uses of quant?
Quant research is useful for describing characteristics of population or market e.g. voting intention, household spending patterns, market and brand share. It is useful for measuring quantifying, validating and testing hypotheses or theories.
Limitations of quant?
Limitations - not flexible - structure and standardisation can produce superficial rather than detailed description and understanding. Closed questions does not allow us to collect answers in respondents own words which can lose ‘real’ responses, detail and context. Can miss out of subtleties in response between respondents how may answer the same thing. These can contribute to low validity.
What is qual?
Typically involves small sample sizes and uses techniques including interviewing, via group discussions, in-depth interviews and workshops, and observations (including ethnography). Concerned with rich and detailed description, understanding and insight rather than measurement. Aims to get below the surface, beyond spontaneous or rational response to the deeper and more emotional response.
Qual limitations?
Limitations - the high flexibility, less structure and standardisation means that this approach is relatively low in reliability, and harder to re-produce at a later date.