topic 7: research methods Flashcards
demand characteristics
when participants know the aim of a research study and alter their behaviour accordingly (to give the results that the researcher wants)
what are experimental designs + list them
only had by experiments (not in observations), they are the different ways to use your participants
- independent measures design
- repeated measures design
- matched pairs design
what is an independent measures design + evaluate
where two completely different groups are assessed
time cost - have to re-explain, if you’re paying them then you might have to pay more people
sample size - needs the double the people of repeated measures
demand characteristics - no reason for demand characteristics
order effects - none
individual differences - most open to difference because there’s no matching between the groups
individual differences
any differences between the participants, they become extraneous variables
participants
your sample, the people that participated in your study
what is a repeated measures design + evaluate it
where the two groups used are identical because they are comprised of the same participants
time cost - if you’re paying them, then it could be cheaper bc there are less people
sample size - smallest
demand characteristics - highest chance because they will see variations of the IV (but counterbalancing is used)
order effects - possible as repeating the test many times may lead to improvement/fatigue
individual differences - least individual difference
what is a matched pairs design + evaluate it
where the two groups are matched on the most important variable (e.g. hair colour/height)
time cost - highest because everyone has to be tested individually and matched
sample size - needs the double the people of repeated measures
demand characteristics - potentially due to the prior tests for matching but unlikely
order effects - none
individual differences - in the middle of the other two
situational variables
anything about the test situation that affects the group
an extraneous variable
e.g. noise/temperature/lighting
participant variables
the individual characteristics that differ and ultimately decide how an individual responds to an environment
an extraneous variable
e.g. background differences, prior knowledge, health, anxiety, mood
how do you create a matched pairs design
- matched based on key variables (eg. gender + age)
- match with a relevant variable (eg GCSEs for memory)
- pretest to allocate (e.g IQ test)
- pair 1st and 2nd, 3rd and 4th etc.
- allocate one from each pair to each condition
what is the benefit of choosing a matched pairs design
it reduces individual differences which are extraneous variables
what is counterbalancing
used with repeated measures designs
1. split the participants into 2 groups
2. give each group IV1 and IV2 in opposite orders
this allows even distribution of order effects
what is randomisation
the process where it is decided whether participants should experience the experimental/control condition by chance when a repeated measures design is used
e.g. names in a hat/random number generator
what is a target population
the group/population that you want to study
your sample is then drawn from the target population
generalisability
the extent of the ability to apply the findings of your study to the general public
(SHS students liking to read ≠ all students liking to read)
random sampling
when all members of a population have equal chances of being selected
names in a hat:
- list out your population
- write all of the names on separate pieces of paper
- fold them and put in a hat
- randomly pick some for group 1
- randomly pick the same amount for group 2
random number generator:
- list out the population
- assign each participant a number
- set the generator to select 15 random numbers, these become group 1
- then eliminate those numbers/names
- set the generator to set a new 15 for group 2
opportunity sample
asking anyone who’s available and fulfils the criteria
(e.g walking into the common room and asking 4 girls and 4 boys)
self-selected/volunteer sample
advertise through newspapers etc. people just ask to be in the study
OR, people may not even know f it’s an experiment and choose whether or not to take part (e.g just leaving a ladder and seeing if people walk under or not)
stratified sample
using ratios and random selection from strata’s to form a mini population
e.g. if 80% of criminals are males and 200 total criminals, 160 should be males
consider things like gender/religion/ethnicity
it is v time consuming but very representative of the population
systematic sampling
- have a random list of your population
- number them
- decide how big your sample will be
- divide population by sample to get N
- use a random number generator to pick your starting person
- choose every nth person to get your sample
confounding variable
a variable that is confirmed to have interfered with the results
extraneous variable
any variable that interferes with a study
standardised procedures
anything that is kept the same
evaluate random samples
+ no researcher bias (they can’t determine who would be better suited)
- takes longer to plan (higher £)
- may accidentally select people with the same characteristics
- people may not want to take part/higher subject attrition
evaluate opportunity samples
+ don’t have to advertise; quick, cheap, easy to obtain
- may be biased, researcher may gravitate towards the more suited individuals
- the findings can’t be generalized to the target population (might have been mostly maths students in the common room at the time)
what is subject attrition
it is the loss of study units from a sample
evaluate self selected/volunteer samples
+ low subject attrition - people feel contracted and are usually committed
+ have to advertise but still minimal work
- biased; confident people often apply, people interested in psychological research often apply, people apply if they think they’d be good at it
evaluate stratified sampling
+ highly representative of population; lets you generalise results and avoid researcher bias 
- Very time consuming+difficult
- we can never fully represent the population (can’t include things like character)
- information can be difficult to find and finding it all and putting it into a random delete or can be v difficult/overwhelming
evaluate systematic samples
+ easy to construct, understand, compare and execute if already listed
+ cheap
+ avoids researcher bias
- assumes everyone is available
- can be difficult if there’s a v big population/no available list
what defines a piece of research as a true experiment
1) the researcher manipulates an IV and keeps all the other variables constant to measure the effect on the DV
2) participants can randomly be allocated to conditions
what are examples of true experiments
laboratory experiments
field experiments
what are examples of not-true experiments
natural experiments (not-trueal)
quasi experiments
what is a laboratory experiment
experiments carried out under controlled conditions; an artificial environment with tight control over variables
what is a field experiment
carried out in the p’s natural environment, but the IV is manipulated by researchers
what is a Quasi experiment
the IV being studied is a pre-existing difference between people (eg. age/gender)
a quasi experiment is often also a lab experiment
what is a natural experiment
when the IV occurs naturally; studying an island before vs after tv in terms of aggression level in kids
pros and cons of laboratory experiments
+ easier to replicate because of standardised procedures
+ allows control of IVs and extraneous variables; allows establishment of a cause and effect relationship
- low ecological validity; may produce unnatural behaviour, so findings can’t be generalised to a real life setting
- demand characteristics/experimenter effects may bias results, could become confounding variables
pros and cons of field experiments
+ higher ecological validity than lab experiment
+ if the study is covert, lower likelihood of demand characteristics
- less control over extraneous variables
- makes it difficult to replicate
pros and cons of natural experiments
+ ethical because it’s natural so you aren’t changing anything
+ very high ecological validity
+ lower likelihood of demand characteristics as p’s might not know they’re being studied
+ can be used when it could be ethically unacceptable to manipulate the IV (eg. stress)
- no control over extraneous variables that could bias the results; difficult to replicate
pros and cons of Quasi experiments
+ they can be used to study things that couldn’t be studied in a different way; eg. gender differences
— the two sample groups have characteristics that are unique to them that could become extraneous variables
since they’re often also lab experiments; can have high control but also higher chances of extraneous variables
objective
no bias is possible
subjective
bias is possible
validity
the extent to which a test measures what it claims to measure
ecological validity
the degree to which an investigation represents real life experiences
experimenter effect
the way in which the experimenter can accidentally influence the participant through their behaviour/appearance
control group
a group that doesn’t receive any manipulation of the independent variable, it can be used to compare with experimental groups
reliability
consistency (doesn’t mean that it’s correct)
what are ethics
a set of guidelines that should be followed by pyschologists that carry out research
what rights do participants in studies have
right to privacy
right to confidentiality
right to withdraw
informed consent
debriefing
what is the right to privacy
the right to not be studied anywhere that privacy would be expected; eg. toilets/at home
what is the right to confidentiality
participants have the right to expect that any information that they provide will be treated confidentially and not be identifiable as theirs if published
what is the right to withdraw
participants have the right to leave a study at any point and ask for their data to be fully erased