Research Methods Flashcards
Define ‘experimental method’
Manipulation of IV to measure effect on DV.
Experiments may be laboratory, field, natural or quasi.
What is the ‘independent variable (IV)’?
Some aspect of the experimental situation that’s manipulated by researcher/changes naturally - so effect on the DV can be measured.
What is the ‘dependent variable (DV)’?
Variable measured by researcher. Any effect on DV should be caused by the change in IV.
Define ‘aim’
A general statement of what the researcher intends to investigate; the purpose of the study.
Define ‘hypothesis’
A clear, precise, testable statement that states relationship between variables to be investigated. Stated at outset of study.
Define ‘directional hypothesis’
States the direction of the difference or relationship.
Define ‘non-directional hypothesis’
Does not state the direction.
Define ‘variables’
Any ‘thing’ can vary/change within investigation. Variables generally used to determine if changes in one thing result in changes to another.
Define ‘operationalisation’
Clearly defining variables in terms of how they can be measured.
What is meant by an ‘extraneous variable (EV)’?
Any variable, other than IV, that may have an effect on DV if not controlled. EVs essentially nuisance variables - don’t vary systematically with IV.
What is meant by a ‘Confounding variable (CV)’?
Any variable, other than IV, may affect DV so can’t be sure of true source of changes to DV. Confounding variables vary systematically with IV.
Define ‘demand characteristics’.
Any cue from researcher/situation that may be interpreted by participants as revealing purpose of investigation. May lead to participant changing behaviour.
Define ‘investigator effects’.
Any effect of the investigator’s behaviour (conscious/unconscious) on DV. May include everything from design of study to selection of, and interaction with, participants during the research process.
Define ‘randomisation’ and give an example.
Use of chance to control for effects of bias when designing materials and deciding order of conditions.
E.G. using random allocation- in an independent groups design with 4 conditions you might randomly allocate your selected participants into each of the groups.
Define ‘standardisation’
Using exactly same formalised procedures and instructions for all participants in research study.
Define ‘experimental design’
Different ways testing participants can be organised in relation to experimental conditions.
What is ‘independent groups design’
Participants are allocated to different groups where each group represents one experimental condition.
What is ‘repeated measures design’?
All participants take part in all conditions of the experiment.
What is ‘matched pairs design’?
Pairs of participants are first matched on some variable(s) that may affect the DV. Then one number of the pair is assigned to Condition A and the other to Conditions B.
Define ‘random allocation’.
Attempt to control for participation variables in independent groups design. Ensures each participant has same chance of being in one condition as any other.
Define ‘counterbalancing’.
Attempt to control effects of order in repeated measures: half experience conditions in one order, and the other half in opposite order.
What is a ‘laboratory (lab) experiment’?
Controlled environment within which the researcher manipulates the IV and records the effect on DV, whilst maintaining strict control of extraneous variables.
What is a ‘field experiment’?
Takes place in a natural setting within which the researcher manipulates the IV and records the effect on the DV.
What is a ‘natural experiment’?
An experiment where the change in the IV is not brought about by the researcher but would have happened even if the researcher had not been there. The researcher records the effect on the DV.
What is a ‘quasi-experiment’?
Study that’s almost an experiment but lacks key ingredients. IV not been determined by anyone (researcher/any other person) - the ‘variables’ simply exist, (old or young) . Strictly speaking - not an experiment.
Strengths of Independent Group Design.
(+) Order effects not problem - participants only experience one condition.
(+) Less likely guess aim as only experience one condition and don’t see any manipulation.
Limitations of Independent Group Design.
(-) Participants who occupy different groups not same. If researcher finds difference between groups on DV it may be due to individual differences (participant variables) rather than IV.
(-) Design less economical than repeated measures as each participant contributes single result only. Twice as many participants needed to produce equivalent data to that used in repeated measures.
Strengths of Repeated Measures Design.
(+) Participant variables are controlled as you compare each participants score in one condition their score in another.
(-) Fewer participants are needed because they take part in more than one condition which means the study is more economical.
Limitations of Repeated Measures Design.
(-) As each participant has to do at least two tasks then the order of these tasks may be significant (i.e. there are order effects e.g. tiredness). Order acts as a confounding variable.
(-) More likely people will work out the aim of the study when they experience all conditions of the experiment. For this reason demand characteristics tend to be more of a feature of repeated measures than independent groups.
Strengths of Matched Pairs Design.
(+) An attempt to reduce participant variables as all participants are matched on important variables.
(+) Participants only take part in a single condition so order effects are less of a problem.
(+) Participants are less likely to guess the aim of the study (demand characteristics) because they only take part in a single condition and see no manipulation.
Limitations of Matched Pairs Design.
(-) Participants can never be matched exactly, even when identical twins are used there will still be some participant variables.
(-) Matching is time-consuming, expensive and requires a larger sample size which makes it less economical than other designs.
Strengths of lab experiments.
(+) High control of extraneous variables so researcher can ensure any effect on DV likely to be the result of the IV. (More certain about cause and effect- internal validity).
(+) Replication more possible than in other types due to the level of control Ensures new extraneous variables not introduced when repeating experiment.
Limitations of lab experiments.
(-) Lack of generalisability- the lab artificial and not like everyday life. In an unfamiliar context participants may behave in unusual ways so their behaviour cannot always be generalised beyond the research setting (low external validity).
(-) Participants are usually aware they are being tested which may give rise to unnatural behaviour or demand characteristics.
(-) Lab based tasks may not represent real life experience which means they will lack mundane realism.
Strengths of field experiments.
(+) Higher mundane realism than lab experiments because the environment is more natural. This means they produce behaviour that is more valid and authentic.
(+) Higher external validity, especially if participants are not aware they are being studied.
Limitations of field experiments.
(-) Loss of control of extraneous variables could mean cause and effect between the IV and DV in field studies may be more difficult to establish and precise replication is not possible.
(-) Ethical issues- if participants are unaware they are being studied they cannot consent to being studied which means research may invade privacy.
Strengths of natural experiments.
(+) Provide opportunities for research that may not otherwise be undertaken for practical or ethical reasons, such as the studies of institutionalised Romanian Orphans.
(+) High external validity because they involve the study of real-life issues and problems as they happen, such as the effects of a natural disaster on stress levels.
Limitations of natural experiments.
(-) Naturally occurring events happen rarely, reducing the opportunities for research. This may also limit the scope for generalising findings to other situations.
(-) Participants may not be randomly allocated to experimental conditions. This means the researcher may be less sure whether the IV affected the DV.
Strengths of quasi- experiments.
(+) Carried out in controlled conditions so have higher internal validity.
(+) Replication is possible because of the high level of control.
Limitations of quasi-experiments.
(-) Participants may not be randomly allocated to experimental conditions. This means the researcher may be less sure whether the IV affected the DV.
(-) Confounding variables are a problem with this design e.g. if comparing older with younger participants then memory would always have an effect on the DV.
Define ‘population’.
A group of people who are the focus of the researcher’s interest, from which a smaller sample is drawn
Define ‘sample’.
A group of people who take part in a research investigation. The sample is drawn from a (target) population and is presumed to be representative of that population i.e. it stands ‘fairly’ for the population being studied.
What are ‘sampling techniques’?
The method used to select people from the population.
What is meant by the term ‘bias’ in the context of sampling?
Certain groups may be over/under-represented selected sample selected. E.g., too many younger people or of one ethnic origin.
Limits extent to which generalisations can be made.
Define ‘generalisation’.
The extent to which findings and conclusions from a particular investigation can be broadly applied to the population. This is made possible if the sample of participants is representative of the population.
What is a random sampling?
Every person in target population has equal chance of being selected.
Lottery method. Number randomly generated (hat/computer).
Strengths of random sampling.
(+) Free from researcher bias. The researcher has no influence over who is selected which prevents them from choosing people who may support their hypothesis.
(+) Produces a representative sample as each member of the target population has an equal chance of being selected.
Limitations of random sampling.
(-) Difficult and time consuming to conduct. A complete list of the target population may be extremely difficult to obtain.
(-) Could still end up with an unrepresentative sample.
(-) Selected participants may still refuse to take part which means you end up with more of a volunteer sample.
What is systematic sampling?
Participants selected using set patter. Every nth person from list of target population.
Strengths of systematic sampling.
(+) Avoids researcher bias, once the system for selection has been established the researcher has no influence over who is chosen.
(+) Fairly representative, it would be possible but quite unlucky to get an all male-sample through this method.
Limitations of systematic sampling.
(-) Selected participants may still refuse to take part which means you end up with more of a volunteer sample.
What is stratified sampling?
Participants selected according to their frequency in the target population.
Subgroups (‘strata’) identified. Relative percentages of the subgroups in the population are the calculated and reflected in the sample.
Strengths of stratified sampling.
(+) Avoids researcher bias, once the target population has been sub-divided into strata, the participants that make up the numbers are randomly selected and beyond the influence of the researcher.
(+) A highly representative sample because it is designed to accurately reflect the composition of the population. This means that generalisation of findings becomes possible.
Limitations of stratified sampling.
(-) Stratification is not perfect, the identified strata cannot reflect all the ways that people are different, so complete representation of the target population is not possible,
(-) Selected participants may still refuse to take part which means you end up with more of a volunteer sample.
What is opportunity sampling?
Those simply available i.e. ones nearest/easiest to obtain.
Ask people nearby - students in class, people who walk past you in shopping centre.
Strengths of opportunity sampling.
(+) Convenient- this method saves the researcher a good deal of time and effort and is much less costly in terms of time and money than other sampling techniques.
Limitations of opportunity sampling.
(-) Unrepresentative of the target population as it is drawn from a very specific area such as one street in a town so findings cannot be generalised to the target population.
(-) Researcher bias is high as they have complete control over the selection of participants so they may select people who will support their hypothesis.
What is a volunteer sampling?
Participants select themselves for the research. Advertise. Place an advert in a newspaper/noticeboard and participants come to you.
Strengths of volunteer sampling.
(+) Requires minimal input from the researcher and so is less time-consuming than other forms of sampling.
Limitations of volunteer sampling.
(-) Volunteer bias is a problem. Asking for volunteers may attract a certain type of person, that is, one who is helpful, keen and curious. This may affect how far findings can be generalised.
What are ‘ethical issues’ in Psychology?
Arise when conflict exists between rights of participants and goals of research to produce authentic, valid and worthwhile data.
What is the BPS code of ethics?
A quasi-legal document produced by the British Psychological Society (BPS) - instructs psychologists in UK about what behaviour is/isn’t acceptable when dealing with participants. Built around four major principles: respect, competence, responsibility and integrity.
What is informed consent?
Participants should be able to make informed judgement about taking part.
Should be made aware of aims, procedure, their rights and also what their data will be used for.
How to deal with informed consent?
Consent letter/form detailing all relevant information that may affect their decision to take part. Agreement - signed. Under 16 require parental consent
What is protection from harm?
Participants should be at no more risk than everyday life.
Protected from both physical and psychological harm.
Includes embarrassment, feeling inadequate or stressed.
How to deal with protection from harm and deception?
Give full debrief. Made aware of true aims and any details not supplied during study (other groups/conditions).
Also told what data will be used for and must be given right to withhold/withdraw. Important if give retrospective consent.
Reassurance of normal/typical behaviour and if severe embarrassment/stress should be given counselling.
What is deception?
Deliberately misleading/withholding info.
If done so participants can’t give fully informed consent. May be justified if doesn’t cause distress..
What is confidentiality and privacy?
Participants have right to control info about themselves.
If privacy invaded, confidentiality should be respected like names and other personal details anonymous under Data Protection Act. Extends to where it takes place like locations aren’t named.
How to deal with confidentiality?
If personal details held, must be protected. However, more usual to simply record no details (maintain anonymity). Refer to participants using numbers/initials like in case studies.
Also standard practice during briefing and debriefing reminded data will be protected throughout process.
What is meant by ‘pilot study’ and why is it useful?
A small-scale version of an investigation that takes place before the real investigation is conducted. The aim is to check that procedures, materials, measuring scales, etc., work and to allow the researcher to maker changes or modifications if necessary.
How are pilot studies important for self-report methods?
E.g., questionnaires and interviews - helpful to try out questions and remove/reword those that are ambiguous/confusing.
How are pilot studies important for observational studies?
Way of checking coding systems before real investigation.
May be important part of training observers.
What is a single-blind procedure?
Details like conditions participants are in kept.
Won’t know if in a condition if there’s another condition.
Attempt to control confounding effects of demand characteristics.
What is a double-blind procedure?
Neither participants nor researcher who conducts study aware of aims.
Important for drug trials.
Treatments administered by someone independent of investigation and doesn’t which drug is real/placebo.
Define ‘naturalistic observation’.
Watching and recording behaviour in the setting within which it would normally occur.
Define ‘controlled observation’.
Watching and recording behaviour within a structured environment, i.e. one where some variables are managed.
Define ‘covert observation’.
Participants’ behaviour is watched and recorded without their knowledge and consent.
