Research methods - PYSA1
- Created by: SarahBennett1997
- Created on: 18-03-14 15:56
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- Research methods - PYSA1
- Week 1: Investigation design
- DV- The variable that is measured
- IV- The variable manipulated or controlled by the experimentor.
- Null hypothesis- The predicion that there is no difference and any difference will be due to chance alone
- Nominal data- frequency something occurs
- Ordinal data- data that can be placed into rank order
- Ratio Data- data generated using set standards
- Pilot study- pre experiment test that checks that the experiment is in working order before the actual research takes place
- Internal Validity- the extent to whihc the experiment is testing what it was meant to
- External validity- the extent to which the finsings can be generalised
- Demand characteristics- particular features of the experiment that may make participants behave in a certain way
- Single blind and double blind procedures
- Random sampling- uses random numbers or computer generators
- Oppurtunity sampling- sampling whoever was availiable
- Voulenteer sampling- involves partivipants who voulenteer
- Ethical issues- Deception, inormed consent, protection of participants, deception.
- Quantitative Data- data measured on a numerical scale
- Qualitative data- extremely varied text data.
- Week 2: Experimental Method
- Lab experiments- allow cause and effect to be established
- Lab experiments- not ecologically valid and artificial
- Field experiments- greater mundane realism than lab experiments
- Field experiments- ethical issues such as informed consent
- Natural experiments- very high ecological validity
- Natural experiments- Cause and effect cannot be established
- Repeated measures- AD: Individual differences are reduced DISAD: order effects can apply
- Independant group design: AD: Less likewly to guess the demand characteristics DISAD: Individual differences
- Matched participants: AD: Individual differences are minimised. DISAD: Difficult and time conduming
- Week 3: The non experimental method
- Alternate hypothesis: Tests for a relationship between two variables
- Correlational Analysis: used when looking at the relationship between two variables. AD: shows direction and strength or relationship DISAD: casuse and effect cannot be established
- Naturalistic observations: observing behaviour in a natural enviroment
- Controlled observations: reseacher sets up a situation to be observed
- Observations: AD- Relitivally easy to do DISAD- ethical issues such as informaed consent
- Questionarres: Gather data by asking a representative sample of poeple the same questions about particular attitudes, opinions calues and beliefs
- Interviews: one to one conversation about personal topics such as thoughts, feelings and behaviours
- Case studies: detailed in depth investigation into a single case , a group of people or an event
- Case study: AD- useful when researching rare/ unique topics DISAD- difficult to generalise results
- Interviews: AD- can yeild rich and in depth data DISAD- researcher bias
- Questionarres: AD- cheap and easy to do. DISAD- participant reactivity
- Week 1: Investigation design
- Aletrnate hypothesis- A clear testable statement about the outcome of the experiment
- Week 1: Investigation design
- DV- The variable that is measured
- IV- The variable manipulated or controlled by the experimentor.
- Null hypothesis- The predicion that there is no difference and any difference will be due to chance alone
- Nominal data- frequency something occurs
- Ordinal data- data that can be placed into rank order
- Ratio Data- data generated using set standards
- Pilot study- pre experiment test that checks that the experiment is in working order before the actual research takes place
- Internal Validity- the extent to whihc the experiment is testing what it was meant to
- External validity- the extent to which the finsings can be generalised
- Demand characteristics- particular features of the experiment that may make participants behave in a certain way
- Single blind and double blind procedures
- Random sampling- uses random numbers or computer generators
- Oppurtunity sampling- sampling whoever was availiable
- Voulenteer sampling- involves partivipants who voulenteer
- Ethical issues- Deception, inormed consent, protection of participants, deception.
- Quantitative Data- data measured on a numerical scale
- Qualitative data- extremely varied text data.
- Week 1: Investigation design
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