research methods

Lab experiments

Carried out in a controlled setting where variables are manipulated/controlled by a research

Participant

An individual that takes part in a piece of research

Independent variable

A variable that researcher changes or investigates to see if it has an effect on another variable

Dependant variable

A variable that a researcher measures to see if it is affected by the indépendant variable

Operationalise

Defining a variable in a way that is measurable for research

Aim

A general statement or purpose of our research

Hypothesis

A testable statement at the start of a study that clearly states the relationship between variables

Validity

whether an observed effect is genuine

Reliability

How consistent an observed effect is

Extraneous variable

Factors that don’t act as an IV but may have an effect on DV

Standardised procedures

A set of instructions that stay the same for all parts of experiment

Internal validity

Extent to which observed effect was due to experimental manipulation rather than other factors

External validity

Extent to which research can be generalised to other settings

Ecological validity

Extent to which research can be applied to real life

mundane realism

how an experiment mirrors the real world

control

extent to which any variable is held constant by a researcher

generalisation

applying findings of a particular study to the population

repeated measures design

each participant completes all the conditions of the IV

repeated measures design strengths and weaknesses

+fewer people so lowers risk of participant variables

-order effects may impact results of study

independant groups design

participants are allocated to two or more groups representing different levels of the IV.

independant groups strengths and weaknesses

+avoids order effects s people participate in one condition only

-more people are needed than in repeated design

-participant variables may affect results

matched pairs design

-a compromise to use two groups of participants but match participants on key characteristics believed to affect performance on the DV.

-one member of the pair is allocated to group a and other to group b

matched pairs strengths and weaknesses

+reduces participant variables and order effects

-time consuming and impossible to match people fully

counterbalancing

used to overcome order effects when using a repeated measures design.

order effect

in a repeated measures design, an extraneous variable arising from the order in which conditions are presented

random allocation

allocating participants to experimental groups or conditions using random techniques

participant variables

characteristics about an individual that may impact a study’s results

field experiment

conducted in a natural setting

the researcher manipulates the IV and measures the DV,

they make every effort to control all aspects of the experiment, but because of the natural setting there may be an extraneous variables

lab experiment

carried out in an artificial setting that is highly controlled. the researcher manipulates the IV and measures the DV

natural experiment

experimenter has not manipulated the IV directly. the researcher records the effect of the IV on the DV which may be measured in a lab

quasi experiment

the IV is actually not something that varies. the researcher records the effect of the quasi IV on a DV.

Lab strengths and weaknesses

+higher control of extraneous variables so more reliable- higher internal validity

+can easily be replicated

+ethically right perhaps as people are aware

-lower levels of ecological validity- in an artificial environment so not representative of real world

Field strengths and weaknesses

+high ecological validity as natural behaviour is reflective of the real world

-reduced reliability as researcher cannot control extraneous variable so lower internal validity

-poorer ethics as people don’t know they’re being studied

Natural strengths and weaknesses

+enables psychologists to study real problems +strong mundane realism and ecological validity

+allows research where IV can’t be manipulated for ethical reasons

-cannot demonstrate casual relationships as IV is not directly manipulated

-random allocation not possible so may not be able to control extraneous variables so lowers internal validity

Quasi strengths and weaknesses

+allows comparisons between types of people

-participants may be aware that they’re being studied so lowers internal validity

-DV may have an artificial task which reduces mundane realism

Controlled observation

A form of investi in which behaviour is observed but under conditions where certain variables have been organised by the researcher

Covert observation

Observing people without their knowledge

Inter-observer reliability

Extent which there is an agreement between 2 or more observations of a behaviour

Naturalistic observation

An observation carried out in everyday setting in which investigator doesn’t interfere in any way but observes behaviours

Non participant observation

Observer is merely watching behaviour of others and doesn’t interact with people being observed

Observer bias

Observers expectations affect what they see or hear

Overt observation

Where participant may be aware that they’re are being studied

Participant observation

Observer is apart of a group being observed

observational studies strengths and weaknesses

+high validity

+capture unexpected behaviour

+often used as a way to measure DV

-observer bias as difficult to be objective

-only observable behaviour is recorded not thoughts or feelings

naturalistic strengths and weaknesses

+gives realistic picture of spontaneous behaviour so increases ecological validity

-little control of all other things happening so something unknown may account for observed behaviour

controlled strengths and weaknesses

+observer can focus on particular aspects of behaviour

-control may make environment feel unnatural so participant may change behaviour

overt strengths and weaknesses

+can give consent

-participants are aware so decreases naturallness

covert strengths and weaknesses

+participants are unaware so behaviour is more natural

-ethical issues as cannot give consent

participant strengths and weaknesses

+observations may provide a special insight to behaviour

-more likely to be overt so issues of participant awareness

non participant strengths and weaknesses

+observers are likely to be more objective

-more likely to be covert and have ethical issues

behavioural categories

dividing target behaviour into subset of specific and operationalised behaviours

event sampling

an observational technique in which a count is kept of the number of times a certain behaviour occurs

sampling

used to select participants, such as random, opportunity and volunteer sampling

structured observation

a researcher uses various systems to organise observations such as behavioural categories and sampling procedures

time sampling

observer records behaviour in given time frame

Time sampling strengths and weaknesses

+less likely to get overwhelmed with observations and recording data meaning events get missed

+less likely to have the problem of ppl doing the same behaviour

-may miss behaviour in the intervals when not observing

Event sampling strengths and weaknesses

+less likely to miss behaviour as you record every event

-more likely to miss behaviour due to many events occurring at once whilst also trying to record observations

-more likely to face the problem if ppl not changing behaviour which may limit observations

Inter observer reliability steps

-another observer will conduct the same observation

-uses the same behavioural categories

-establish agreement between observers scores

-should have agreement of +0.8

Behavioural categories

Target behaviours divided into subsets using coding systems

-should be objective, cover all possible component behaviours and be mutually exclusive

Questionnaire

Set of written questions that is designed to collect info about a topic

Structured interviews

Pre determined questions that are delivered face to face with no deviation from original questions

Unstructured interviews

Less structured

Questions develop during the course of the interview

Social desirability bias

A distortion in the way people answer questions in a way where they present themselves in a better light

Self report strengths and weaknesses

+allow access to what people think and feel to their experiences and attitudes

-may not be truthful-social desirability bias

-people don’t always know how they feel-lack validity

-people used may lack representativeness

Questionnaire strengths and weaknesses

+once designed, can be distributed to large number of people relatively cheaply and quickly

+respondents are more willing to give personal info in questionnaire

-only filled in by people who can read or write or have time to answer- biased

Structured interview strengths and weaknesses

+can be easily repeated as questions are standardised

+easier to analyse than structured as more predictable

-comparability may be an issue if the interviewer behaved differently so reduces reliability

-interviewers expectations may influence answers given- interviewer bias

Unstructured interview strength and weaknesses

+more detailed info obtained from respondents

-requires skilled interviewers- expensive

-questions may lack objectivity due to instantaneous nature

A good question includes

Clarity

Bias

Analysis

A good questionnaire should consider

Filler questions

Sequence for questions

Sampling method

Pilot study

Correlation hypothesis

-No IV or DV instead co-variables

-can be directional or non directional

Directional hypothesis

There will be positive correlation between age and income

Non directional hypothesis

There’ll be a correlation between age and income

Null correlation

There’ll be no correlation between age and income

Correlation coefficient

A number calculated from the participants data that will be between -1 and 1

-closer to -1 or 1 means strong correlation

Correlation strengths and weaknesses

+used to investigate trends in data-if correlation is significant then further investigation is justified

+procedures can be easily tested

-variables are simply measured so no conclusions can be made about one co variable causing the other

-people assume natural conclusions

-casual connections may be due to intervening variables

-a correlation may lack internal or external validity

Case study

A research investigation that involves a detailed study of a single individual, institution or event

Content analysis

A kind of observational study investigation which behaviour is observed indirectly in written or verbal material

Effect size

A measure of the strengths of the relationship between two valuables

Meta analysis

Researcher looks at findings from a number of different studies and produces a statistic to represent overall effect

Review

A considerations of a number of studies that have investigated the same topic in order to reach a general conclusion about a particular hypothesis

Meta analysis strengths and weaknesses

+reviewing from a group of studies rather than one increases validity

+meta analysis allows us to reach an overall conclusions by having a statistic to represent the findings of different studies

-studies are not always truly comparable

-putting them all together to calculate the effect size may not be appropriate so conclusions aren’t always valid

Case study strengths and weaknesses

+offers rich and in depth data

+useful as investigates rare human behaviour and experiences

+complex interaction on many factors can be studied

-difficult to generalise from individual cases as each one has unique characteristics

-often involves recollection of past events as part of the case history and evidence may be unreliable

-only identified after key event

Directional hypothesis

Based on previous research

Predicts which of the two conditions will result in a greater change in DV

Non directional hypothesis

Direction is not predicted

Happens when there’s no previous research

Null hypothesis

Must be able to contradict the experimental hypothesis

Refers to the probability that the results are due to chance

Extraneous variables

Factors which influence the DV other than the IV but do not affect DV

Demand characteristics- extraneous variable

Pps acting in cues or looking for clues that influence how they behave

Behaviour is no longer natural

Investigator effects- extraneous variable

Involves anything that investigator does that has an effect on a pps performance

Direct- smiling or indirect-design of study

Participants variables-extraneous variables

Certain characteristics associated with pps e.g age, intelligence

Situational variables- extraneous variables

Factors associated with the environment I.e noise, lighting

Randomisation

Use of chance wherever possible to reduce investigator effects on the result of the study

Standardisation

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

Consequences of not controlling extraneous variables

Lack of internal validity

Population

A large group of people that you are interested in studying

Target population

A specific group of people you want to study

Informed consent

Participants are aware of the aims of the study and consent to take part

Deception

Participants are not fully aware of the aims of the study

Privacy

Ensuring participants only observed in a place they’d expect to be observed

Protection from harm

Participants experience distress or physical pain

Confidentiality

Ensuring participants identity is protected