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Overview of Research Methods
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Research methods
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a levels
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Suz
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Overview of Research Methods
Types of data
Primary Data- collected by researcher themselves.
Secondary Data- Collected by someone else, used by researcher.
Quantitative Data- Numerical.
Qualitative Data- Written/ Spoken, other forms (e.g. photos)
Practical Issues
Time and money- Some methods are more costly or time consuming.
Requirements of funding bodies- those funding research may select the topic + type of data and the presentation
Personal skills & characteristics- May affect the choice of method. E.g. May struggle to establish the rapport with interviewees.
Subject matter- Some topics/groups may be harder to study than others.
Research opportunity- If there is an unexpected opportunity for research, time consuming methods (e.g. Questionnaires) won't be able to be used.
Ethical issues
Informed consent- All participants have to agree to take part, being fully aware of what the research is about.
Confidentiality & Privacy- Mustn't reveal names or personal details of participants.
Effects on research participants- Must avoid physical or mental harm on participants.
Vulnerable groups- Extra care when working with certain groups i.e. children, elderly, victims of crime or mentally ill.
Covert research- Some argue it's unethical as people are unaware they're being studied, however can be the only way.
Theoretical issues
Validity- Method which produces a true picture.
Reliability- Consistent results when repeated.
Representativeness- Sample is cross-section of the wider group the researched is based on.
Methodological perspective- Positivists prefer quantitative data; Interpretivists prefer qualitative data.
Theoretical perspective- Social action (Micro) perspectives prefer qual. methods for meaning; Structural (Macro) perspective prefer quant. methods for society shaping behaviour.
Quantitative or Qualitative
Positives- Quantitative: High reliability, Bigger samples, Generalisation, and Predictions of behaviour.
Interpretivists- Qualitative: High validity, More detailed; However smalls samples so hard to generalise.
Triangulation- Combing different methods (e.g. Quant. + Qual.)
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