Research Methods

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Experimental Method

Aims: the purpose of the investigation

Hypothesis: the formulation of a testable statement

Directional: Identifying a difference/correlation or not

Non-Directional: One-tailed and two-tailed predictions

Variables

IV and DV- IV is manipulated(x) and DV is measured(y)

Levels of IV- experimental and controlled conditions

Operationalisation- adding units e.g. cm, m, seconds, hours

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Control of Variables

Extraneous Variables- Nuisance variables but randomly distributed 

Confounding Variables- vary systematically with IV

Demand characteristics- participants second guess the aim of the experiment and alter their behaviour

Investigator effects- The unconscious influence of the researcher's influence

Randomization- The use of chance to reduce the researchers influence

Standardisation- ensuring all participants are subject to the same experience.

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Experimental Design

Types of design- Independent groups- Participants in each condition of an experiment are different (either experimental or controlled)

Repeated measures- All participants take part in all conditions (Both experimental and controlled)

Matched pairs- Similar participants put in pairs and allocated to different experimental conditions

Evaluations- Independent groups- Less economical, No order effects, Participant variables are not controlled

Repeated measures- Order effects, Demand characteristics, No participant variable problems, more economical

Matched pairs- No order effect, cannot match participants exactly, Time consuming.

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Types of Experiment

Lab experiment- IV is manipulated in a controlled setting

Field experiment- IV is manipulated in a natural setting

Natural experiment- IV has been naturally manipulated, effect on the DV is recorded

Quasi-experiments- IV based on an existing difference between people, effect on DV is being recorded 

Evaluation: Lab experiments- High internal validity(control), Low external validity(Low realism), cause and effect, replication, demand characteristics.

Field experiments-Lower internal validity, Higher external validity(High realism), Ethical issues

Natural experiments- Low internal validity(no random allocation), High external validity, Unique research(not applicable), opportunity may be rare

Quasi-experiments-Low internal validity(no random allocation), High external validity

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Sampling

Random Sampling- all members of the population have an equal chance of being selected

Systematic Sampling- selecting every nth person from a list

Stratified Sampling- sample reflects the proportion of people within different population strata

Opportunity sampling- choosing whatever is available

Volunteer sampling- Participants 'self-select'

Evaluation: Random Sampling- No researcher bias, Time-consuming, May end up being a biased sample

Systematic Sampling- No researcher bias, Usually fairly representative, May end up with Biased sample

Stratified Sampling- No researcher Biased, Representative, cannot account for all sub-groups

Opportunity Sampling- Convenient, Researcher bias, Unrepresentative

Volunteer Sampling- Less time-consuming, Attracts a certain profile of person

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Ethical Issues and Ways of dealing with them

Ethical Issues: Informed consent- advising participant of what is involved, may reveal the aim.

Deception- telling the truth

Protection from harm- Minimising psychological and physical risk

Privacy and Confidentially- Protecting personal data

Evaluation:Informed consent- Get permission.Presumptive, prior general, retrospective.

Deception/Protection from harm- Debriefing(right to withdraw data) researcher has to provide counselling if needed.

Privacy and confidentiality- Maintaining anonymity, use number not names.

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Observational Techniques

Naturalistic Observations- Behaviour observed where it would naturally take occur. No control variables.

Controlled observations- Some control over the environment, including manipulation of variables to observe effects.

Covert and Overt observation- Observing participants without or with their knowledge

Participant and Non-Participant- To join the group or remain an outsider.

Evaluation:Naturalistic Observations- Low internal validity(Control is difficult), high external validity(especially when covert)

Controlled Observations- Low internal validity, though some extraneous variables may be controlled, High external validity (especially when covert)

Covert and Overt Observations- Covert: Low participant reactivity but ethically questionable. Overt:Behaviour may be affected

Participant and Non-Participant- Participant: Increase external validity but may 'Go native' Non-Participant: More objective but less insight.

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Pilot Studies and MORE

Pilot Studies- Checking procedures and Materials, Making modifications

Single Blind- Participants aren't made aware of research aims until the end

Double-Blind- Neither Participant nor the individual conducting the research knows the aim beforehand

Control group/Condition- Used as comparison

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Observational Design

Designing Observations: Unstructured and Structured- Researcher records everything(Unstructured) or controls what is recorded(Structured)

Behavioural Categories- Target behaviours are broken into observable components

Sampling Methods- Continuous. Event sampling: Count events. Time sampling: Count at timed intervals.

Evaluations: Unstructured and structured- Unstructured: more information but may be too much, qualitative data harder to analyse. Structured: May miss behaviours.

Behavioural Categories- Must be observable, Avoid dustbin category, No Overlap

Sampling Methods- Event: Useful for infrequent behaviour, may miss complexity. Time: Less effort but may not represent whole behaviour.

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Self Report Techniques

Questionnaires- Pre-set list of written questions

Close and Open Questions- Fixed number of answer or not

Evaluations: Questionnaires- Can distribute to many people. Easy to analyse. Social desirability bias. Acquiescene Bias.

Closed and Open questions- Produces quantitive or qualitive data, affected ease of analysis.

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Data analysis: Kind of data

Qualitative Data- Written, Non-numerical description of the participants' thought, feelings or opinions.

Evaluation- Rich in detail, Greater external validity, Difficult to analyse, Conclusions may be subjective

Quantitive Data- Expressed numerically rather than in words.

Evaluation- Easy to analyse, Less biassed, Narrow in scope

Primary Data- collected first hand from the participants for the purpose of the investigation.

Evaluation- High validity, Targets relevant information, Time consuming

Secondary Data- Collected and analysed by someone else and not the researcher

Evaluation- Inexpensive and easy to access, Variation in quality, Outdated and incomplete

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Self Report Design

Designing Self-Report

Questionnaires- Likert scales, Rating scales, fixed choice option.

Interviews- Standardised interview schedule, to avoid interviewer bias, awareness of ethical issues

Writing Good Questions

Overuse of Jargon- Don't be too technical

Emotive language and Leading questions- replaced 'loaded' words and phrased with neutral ones

Double-Barrelled questions and Double negatives- Ask one question only in a clear way.

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Correlations

Correlations: Types of correlation- Postive, Negative, and Zero.

The difference between correlations and experiments- No IV and DV. No manipulation of variables.

Evaluation

Strengths: a Useful Preliminary tool. Quick and economical to carry out, using secondary data.

Limitations: Cannot demonstrate cause and effect. The third variable problem (Intervening Variable). Misuse and misinterpretation. 

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