Psychology research methods

Experiment definition

Investigation looking for a casual relationships in which the Independent Variable is manipulated and is expected to be responsible for changes to the dependent variable.

Three types of experiments

Labratory, field, natural

Labratory experiment

A research when there is IV, DV and strict controls. Looks for a casual relationship and is conducted in a setting which is not the usual environment for the participant with regard to the behaviour they are performing.

Field experiment

Normal environment for the participant with regard to behaviour they are performing. The researcher has control over a few variables, but it is difficult to control the variables.

Natural experiment

A investigation looking for a casual relationship, where the IV cannot be directly manipulated by the experimenter. Study the effect of an existing difference or change. Not true experiment, experimenter cannot manipulate the levels of IV.

Strengths of Lab experiments

High levels of standardisation, and therefore can be replicated easily. High levels of control, and researchers can be more confident that IV is directly affecting the DV.

Weakness of Lab experiments

Artificial environment hence it lacks ecological characteristics, participants may show demand characteristics

Strengths of field experiments

Realistic setting hence ecological validity, limited demand characteristics so behavior is more natural

Weakness of field experiments

Situational variables are difficult to control so it is tough to know if the IV is affecting the DV, issues in breaking ethics since the participants do not know that they're taking part in a study

Strengths of natural experiment

High ecological validity because the IV is naturally occurring, valid representation of a person's behavior

Weakness of natural experiment

Difficult to know whether the IV caused an effect on the DV, difficult to replicate to test for reliability as the event is naturally occuring

Experimental condition

One more of the situations in an experiment which represent the different levels of the IV and are compared

Control condition

situation where the IV is absent.

Questionaires

Research method, mainly written to gain information from participants

Four types of questionaires

Likert, rating, open, closed

Three types of interviews

structured, semi-structured, unstructured

structured

Interviews with a fixed order that may be scripted. (Consistency might be required, and therefore these are standardized)

Semi-structured

Fized list of question, but could deviate to get details

Unstructured

Most questions depend on the respondents answers

Strengths of questionaires

Participants are more likely to give truthful answers as it does not involve talking to someone face to face. Large sample can be answered in a short period, increasing representativenesss and generalizability

Weakness of questionaires

Participants may give socially desirable answers, too many questions may force an answer that does not reflect the participant's opinion

Case studies

A detailed investigation of a single instance that produces an in-depth data specific to that instance

Strengths of case studies

Researchers can focus on one individual, collect rich, in-depth data which adds validity to the findings. High ecological validity as participants are studied in their everyday lives

Weaknesses of case studies

As the research is focused on one person, the case is unique which makes generalisations difficult, Attachments may be formed between researcher and participant which may reduce objectivity of data collected and analysis.

8 types of observation

covert, overt, participant observer, non-participant obser, structued/unstructured, naturalistic/controlled

participant observer

one who watches from the perspective of being part of the social setting of the participant

non-participant observer

does not become involved in the situation being studied

Structured observation

The observer records a limited range of behaviours

unstructured observation

Observer records a range of behaviours, confined to a pilot study to refine the behavioural categories

Naturalistic observation

Study conducted by watching the participants behviour in their normal environment without interference from the researcher in either the social or physical environment

Controlled observation

Watching the participants behaviour in which the social or physical environment has been manipulated by the experimenter

Strengths of observation

If participants are unaware of the obseration - increases ecological validity, data can be alaysted statistically with minimal bias

Weakness of observation

Not aware, may not act naturally but show more socially desirable behaviour, reducing the validity. Difficult to replicate the study, if it is naturalistic as many variables cannot be controlled which reduces the reliability

Strengths of Participant Observation

High ecological validity as participants are observed in real-life setting, as participants are observed in real-life settings. As the observers become involved with the group, likely to understand the motives and reasons for behavior; increasing validity.

Weakness of participant observation

Ethical problems of informed consent, prescence of an outsider can change the behaviors of the group members. This lowers the validity of findings

Strengths of non-participant observation

Participants behaviour will not be affected as the observer is out of sight, observations are more likely to be objective as they are detaching from the people they are observing

Weakness of non-participant observation

difficult to make detailed observations and produce qualitative data that allows understandings to why the behaviours are occurring.

Strengths of structured observation

Behavioral checklist allows objective quantiative data to be collected which then can be analysed statistically

Weakness of structured observation

Sampling of observed behavior tends to be restricted and does not give an idea of the reasons as to why the behaviours are occuring

Strengths of unstructured observation

They can generate in-depth, rich quantitative data that can explain why behaviours are occuring

Weakness of unstructured observation

Observers may easily be drawn to eye catching behaviours and hence may not fully represent all the behaviors

Strengths of naturalistic observations

Participants are unaware that they are being watched, behave more naturally, removing the chances of demand characteristics. High ecological validity as the observation takes place in a natural setting

Weakness of naturalistic observation

Very little control over extraneous variables, makes it difficult to draw a cause and effect relationship. Replication may be difficult as there cannot be a totally standardised procedure, hence making it difficult to test for reliability

Strengths of controlled observation

As set up is controlled, observers can be more confident about what is causing the behaviours. Less chance of extraneous variables affecting participants behaviour

Weakness of controlled behavior

An artifical situation can easily influence participants behaviour. Low ecologi al validity as the setting is artifical

Correlations

Statiistical technique that measures the extent which two variables are related. This analyses the relationship between co-variables, maybe establish a casual relationship between two measured variables. A change in one variable can correspond with a change in the other.

Strengths of correlations

Establishes a cause and effect relationship, do not require any manipulation so can be used where experiments are unethical or impractical

Weaknesses of correlations

Issues of casuality because there could be a third variable affecting the changes. Correlations are restricted that are quantitative so they cannot be used to measure why behaviours are occuring.

A directional hypothesis

Statement predicting the direction of the relationship between two variables

Non-directional

Hypothesis predicting only that one variable will be related to the other

Null hypothesis

testable statement stating that any difference or correlation in the results is due to chance

Independent variable

Factor under invesstigation in an experiment which is manipulated to create two or more conditions and is expected to be responsible for changes in the DV

Dependent variable

Factor which is measured and is expected to change under the influence of the independent variable

Operationalisation

definition of variables so that they can be manipulated, measured, quantified and replicated

Experimental design

Participants are allocated to the different levels of IV

Independent measures design

Experimental design in which different group of participants is used for each IV level, if the IV is naturally occuring, researcher must use it.

Repeated measures design

Experimental design in which participants perform at each IV level, cannot be used if IV is naturally occuring.

Matched pairs design

Experimental design in which participants are arranged in pairs, each pair is similar in important ways to the study, and one member performs at a different level of the IV

Strengths of independent measures design

As participant take part in one condition, they are less likely to guess the aim of the study, reducing the effects of demand characteristics. No order effects that can reduce the validity of findings

Weaknesses of Independent measures design

There may be participant variables affecting the DV rather than the IV. More participants are required for this type of design as a compared to repeated measures.

Strengths of repeated measures design

They eliminates any participant variables as all of them take part in all conditions, fewer participants are needed as compared to independent measures

Weaknesses of repeated measures design

There is a chance of demand characteristics as participants may work out the aim or change their behaviour. Order effects can affect the findings of the study and reduce it's validity. This could be overcome using counterbalancing

Strengths of matched pairs design

May help control individual differences for results. This design is suited better when a repeated measures design may not work due to an order effect that may affect result

Weaknesses of matched pair designs

Trying to match participants similar traits is very time consuming. Trying to match people is impossible as there will be individual differences from one person to another. The study may lack internal validity if these differences affect the IV rather than the experimental condition. The sample may be smaller as trying to find a large sample of people matching traits may be difficult, findings may lack external validity

Extraneous variable

Variable which acts randomly affecting the levels of the IB, or systematically, affecting the DV in all levels of the IB, or or one level of IV

Situational variable

confounding variable caused by an aspect of the environment

Participant variables

confounding variables caused by individual differences of participants

Strengths of qualitative data

gives in depth, detailed accounts given in the words of participants are collected. Understand why participants think, feels or acts in a particular way

Weaknesses of qualitative data

Interpretation of data could be subjective as these are words rather than numbers. Researcher bias - researcher select data that fits into the hypothesis or aim

Strengths of quantiative data

Allows for easier comparison and statistical analysis, numerical data are objective and scientific, minimal chance of psychologists miscalculalting the data and drawing invalid conclusions

Opportunity sampling

When the participants are chosen because they are available at the time and place where the research is taking place

Volunteer samplling

Participants are invited to participate in studies via advertisements

Random sampling

All population members are allocated numbers and a fixed amount of these are chosen unbiasedly

Strengths of opportunity sampling

Large number of participants can be obtained relatively quickly and easily because researchers use people who are around

Weakness of opportunity sampling

Researchers are unlikely to gain a wide variety of partiricpants to allow for generalisation

Strengths of volunteer sampling

Participants are more likely to participate if they have already volunteered, drop-out rate should be lower, making generalisations stronger.

Weaknesses of volunteer sampling

Unable to gain a wide variety of partricipants to allow for generalisation because participants will only be of a certain type

Strengths of random sampling

Researchers can generalise the target population with more confidence

Weakness of random sampling

Obtaining details of the target population to draw the same may be difficult - not representative.

Validity

extent to which the researcher is testing what they claim to be testing

Internal validity

how well the experiment controls confounding variables. Allows researcher to be more confident about casual relationship

Ecological validity

How well an experiment controls confounding variables - allows the researcher to be more confident about the casual relationship

Mundane realism

Extent to which a task represents the real-world situation

Face validity

Measure of validity indicating whether a measure appears to test what it claims to

Concurrent validity

When a test correlates well with a measure that has previously been validated

Generalisability

How widely the findings of a study apply to other settings and population

Demand characteristics

Features of an experiment that give away the aims. This could cause participants to change their behaviour and hence reduce the validity of the study

Objectivity

Unbiased viewpoint that is not affected by an individuals feelings, beliefs, or experiences, so should be consistent between different researchers. This would increase the validity of the study

Subjectivity

Personal viewpoint which may be biased by one's feelings, beliefs or experiences and may differ between researchers. Since this is not consistent, it would reduce the validity of the study

Reliability

Extent to which a procedure, task or measure is consistent

Internal reliability

refers to whether the procedures are standardised so that each participant experiences the same thing