Psychology: Research Methods

Experimental method - Manipulating an independent variable to measure the effect on the dependent variable. Experimenta may be laboratory, field, natural or quasi.

Aim - A general statement of what the researcher intends to investigate: the purpose of the study.

Hypothesis - A statement that states the relationship between the variables to be investigated.

Directional hypothesis - States the direction of the difference or relationship.

Non-directional hypothesis - Does not state the direction.

Variables - Anything that can vary or change within an investigation.

Independent variable(IV) - The variable that is manipulated by the researcher so that the effect on the DV can be measured.

Dependent variable(DV) - The variable that is measured by the researcher.

Operationalisation - Clearly defining variables in terms of how they can be measured.

Extraneous variable(EV) - Any variable, other than the IV that can have an effect on the DV if not controlled. EV's don't vary systematically with the IV.

Confounding variables - Any variable, other than the IV that may have affected the DV so we cannot be sure of the source of changes to the DV. Confounding variables vary systematically with the IV.

Demand characteristics - Any cue from the researcher or the research situation that may be interpreted by participants as revealing the purpose of the investigation. This may lead to the participant changing their behaviour within the research situation.

Investigator effects - Any effect of the investigator's behaviour on the research outcome. This may include everything from the design of the study to the selection and interaction with participants during the research process.

Randomisation - The use of chance in order to control for the effect of bias when designing materials and deciding the order of conditions.

Standardisation - Using exactly the same formalised procedures and instructions for all participants in a research study.

Experimental design - Different ways in which the testing of participants can be organised in relation to experimental conditions.

Independent groups design -  Participants are allocated to different groups where each group represents one experimental condition.

Repeated measures design - All participants take part in all conditions of the experiment.

Matched pairs design -  Pairs of participants are first matched on some variables that may affect the DV. Then, one member of the pair is assigned to condition A and the other to condition B. Participants can be matched on characteristics such as gender, age or IQ.

Random allocation - An attempt to control participant variables in the independent groups design which ensures both participants have an equal chance of being in one condition as in any other.

Counterbalancing - An attempt to control order effects in a repeated measures design. Half the participants experience the conditions in one order, and the other half in the opposite order.

Independent groups
Advantages: Order effects are not a problem
                   Less chance of demand characteristics
                   Minimises attrition (drop-out rate)

Disadvantages: Less economical as each participant contributes single result only
                       Inidivdual differences in results, making them harder to compare and generalise

Repeated measures
Advantages: More economical, as you don't need as many participants
                   No individual participants, as participant variables are controlled

Disadvantages: Order effects can occur, for example boredom, practice effect and fatigue.
                       Demand characteristics are more likely to occur

Matched pairs
Advantages: No order effects or demand characteristics
Disadvantages: Participant variables/ Time consuming+expensive/ Less economical

Laboratory experiments - An experiment that takes place in a controlled environment, where IV is manipulated and DV is recorded. It maintains high control of extraneous variables, and doesn't have to be carried out in an actual lab.

Strength: High control over extraneous variables. Any effect on the DV is likely to be due to the manipulation of IV. Cause and effect can be established, showing high internal validity. Replication is more possible.
Limitation: May lack generalisability. The lab environment is artificial and will not reflect real-life, and the participants might behave in unusual ways. Demand characteristics are more likely to occur, and the task might not reflect real-life = low mundane realism.

Field experiments - An experiment that takes place in a natural setting where IV is manipulated and DV is recorded. 

Strength: Higher mundane realism as the environment is more ntatural. The behaviour will be mor e authentic = high external validity and realism.
Limitation: Loss of control over extraneous variables, much more difficult to establish cause and effect. Ethical issues if privacy and consent isn't assured.

Natural experiments: Where the change in IV isn't brought by the researcher, it happens even if the researcher isn't there. The researcher records the effect on the DV.
Strength: Provides opportunities for research thay may not be usually undertaken for example for ethical reasons,eg. Romanian orphans. Also have high external validity as real-life issues are studied as they happen.
Limitations: Events might happen rarely, reducing opportunities for research and limiting generalisability. Participants might not be randomly allocated to experimental conditions, meaning there is less certainity regarding whether it was the IV affecting the DV. With Romanian orphans, the IV was whether the children were adopted early or late however factors like attractiveness might lead to a less chance of adoption.

Quasi-experiments: Almost an experiment, but lacking key ingredients. The IV isn't determined by anyone and the 'variables' simply exist, such as being old or young.
Strength: Usually carried out under controlled conditions and may share the strengths of a lab experiment.
Limitations: Cannot randomly allocate participants to conditions and may result in confounding variables.

A population is a group of people who are the focus of the researcher's interest, and from this a smaller sample is drawn.

A sample is a group of people drawn from a target population, ideally representative of that population.

Random sample - All members of the population have an equal chance of being selected.(drawing names out of a hat or a computer system)
Strength: No researcher bias as no influence over who is selected.
Limitations: Difficult and time consuming to conduct. A complete list of target population might be difficult to obtain. It is still possible to obtain a freak sample - one that is unrepresentative. Also, selected participants might refuse to take part.

Systematic sample - Every nth member of the target population is selected. A sampling frame is produced.
Strength: No researcher bias. Once the system is established the researcher has no control over who is being chosen. Usually fairly representative.

Stratified sample - Sophisticated form of sampling in which the sample reflects the proportions of people in certain sub-groups(strata). The proportions are worked out and them random sampling is used.
Strength: No researcher bias. Representative sample and generalisable.
Limitations: Cannot reflect all the ways people are different = complete representation isn't possible.

Opportunity sample - Selecting anyone who happens to be willing and available.
Strength: Convenient, less costly than random sampling in terms of time nad money.
Limitations: Researcher bias as in control of who is being selected. Also, unrepresentative as the sample is only drawn from a very specific area. 

Volunteer sample - Participants self-selecting themselves to be a part of the sample, for example through newspapers.
Strength: Easy and less time consuming as it requires minimal input from the researcher,
Limitations: Volunteer bias - certain 'profile' of a person might be attracted, e.g. those who are helpful, keen and curious.

Ethical issues are those that arise when a conflict exists between the rights of participants in research studies and the goals of research to produce authentic, valid and worthwhile data.

BPS code of ethics is a quasi-legal document produced by the British Psychological Society that instructs psychologists in the UK about what behaviour is and is not acceptable when dealing with participants. It is built around respect, competence, responsibility and integrity.

Informed consent involves making participants aware of the aims,procedures of the research and their rights, including right to withdraw. They should then decide whether they want to take part or not. This makes the research unnatural as the participants will know the aim of the study.

Deception is deliberately misleading or witholding information from participants. The participants therefore cannot give consent. Deception can be justified when no distress is caused.

Protection from harm includes embarrassment, stress, harm or pressure.

Privacy and confidentiality is making sure names are hidden and data is anonymous. Institutions and geographical locations should not be named either.

The BPS code of ethics ensure that the guidlines are matched very closely to ethical issues; they're implemented by ethics committees in research institutions who often use a cost-benefit approach to determine whether particular research proposals are ethically acceptable.

Informed consent can be dealt with with a consent form. For investigations involving children under 16, parental consent is required.

Deception is dealt with using a debrief form. Right to withdraw data is also given. 

Protection from harm is dealt through counselling sessions, provided by the researcher, given that stress and embarrassment has been caused.

Confidentiality issues are dealt with through anonymity, and  briefing/debriefing during which participants are told that their data was and will be protected throughout the process.

A pilot study is a small-scale version of an investigation that takes place before the real investigation is conducted. This is to check that the procedure works, allowing the researches to make changes if necessary.

Single-blind procedure is when participants are not told the aim of the research at the beginning of the study. This is done in an attempt to control confounding effects of demand characteristics.

Double-blind procedure is when neither the participants nor the researcher conducting the experiment is aware of the aims of the investigation. This is often used during drug trials with real drugs and placebos.

Naturalistic observation is watching and recording behaviour in a natural setting, where the behaviour normally occurs.
-High external validity as the findings can be applied to real-life, making replication and generalisation easier.

Controlled observation is watching and recording behaviour in a structured environment, for example where variablesare managed.
-Produce findings that cannot be applied to real-life, but extraneous variables are more controlled so observation becomes easier.

Covert observation is when participants' behaviour is watched and recorded without them knowing.
-No problem of participant reactivity, it is valid as observed behaviour is natural. Ethically unacceptable as private life is observed.

Overt observation is when participants' behaviour is watched and recorded with their knowledge.
-More ethically acceptable but knowing they're observed may act as an influence over behaviour

Participant observation is when the researcher becomes a member of the group whose behaviour they are watching.
-This gives the researcher an increased insight into the lives of those studied. This increases the validity. However, the researcher might become over-involved and might lose objectivity.

Non-participant observation is when the researcher remains outside of the group they are watching.
-Allows the researcher to maintain an objective psychological distance, however, they may lose the valuable insight they could've gained in a participant observation.

The researcher might simply want to write down everything they see, which is called an unstructured observation. This observation tends to produce results that are rich in detail.
-A limitation of unstructured observations is observer bias. For example, the researcher might only record the events that catch their eye.
-They benefit from richness in detail. This can be a strength but also a limitation as it makes this sort of qualitative data difficult to compare.

Structured observations are those where target behaviours are first simplified. Then, the researcher will quantify the behaviours using a pre-determined list of behaviours.
-A limitation of structured observations is that detail might be missed by narrowing down what the researcher is looking for.
-A strength is that it produces quantitative data which is easier to compare.

Before an observation, it is necessary to break up the target behaviour into a set of behavioural categories, similar to operationalisation. For example, 'affection' can be broken down into hugging,kissing,smiling and holding hands.
-A strength is that it makes data collection more structured and objective.
-Researcher are to ensure the categories are exclusive and don't overlap.

Event sampling - counting the number of times a particular behaviour occurs in a target individual.
-A strength is that event sampling is useful when the event happens infrequently and could be missed if time sampling was used.
-A limitation is that important details could be missed if the specified evet is too complex.

Time sampling - recording behaviour within a pre-established time frame, eg. every 60 seconds.
-A strength is that it is effective in reducing the number of observations.
-A limitation is that those instances where behaviour is sampled might not be representative of the observation as a whole.