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
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
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.
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.
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
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
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.
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.
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
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.
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.
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
Self Report Design
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.
Correlations: Types of correlation- Postive, Negative, and Zero.
The difference between correlations and experiments- No IV and DV. No manipulation of variables.
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.