Research Methods: Strengths + Weaknesses Flashcards
Strengths of Repeated Measures Design
individual differences are removed compared to individual groups
Weaknesses of Repeated Measures Design + how to deal with them
- order effects: order of conditions could affect performance: short break, two different tests, counter balancing: ensures each condition is tested first or second in equal amounts
- demand characteristics: ps guess aim of study and alter behaviour: single blind study: ps dont know true aim
Strengths of Independent Group Design
no order effects
Weaknesses of Independent Groups Design + how to deal with them
- no control of ps variables
- need twice as many ps
- randomly allocate ps to conditions to ensure theyre equivalent
- match ps
Strengths of Matched Pairs Design
- controls some p variables
- ps wont guess aim
- no order effects
Weaknesses of Matched Pairs Design + how to deal with them
- difficult and time consuming
- may be too costly
- may not control all variables
- restrict number of varibales to be matched on
- pilot study could show key variables that need to be matched
Strengths of Random Sampling
unbiased: all members of target population have equal chance of being selected
Weaknesses of Random Sampling
need to have a list of everyone in population and then contact those selected: takes time
Strengths of Opportunity Sampling
- easiest method
- reduces costs and time taken to find ps
Weaknesses of Opportunity Sampling
drawing sample from such a small part of population will prodcue bias
Strengths of Stratified Sampling
most representative of all methods as sample is proportionate to subgroups and random
Weaknesses of Stratified Sampling
very time consuming to identify subgroups and randomly select ps and then contact them
Strengths of Systematic Sampling
unbiased as ps are selected using an objective system
Weaknesses of Systematic Sampling
not truly unbiased/random unless you start with a random method for selecting the first ps and then select every nth person
Strengths of Volunteer Sampling
wide variety of people which may make sample more representative
Weaknesses of Volunteer Sampling
sample may be biased towards people who are motivated/confident or need money resluting in a volunteer bias
Strengths of Lab Experiment
- easy to replicate: increases external validity
- good control over IV and DV: less extraneous variables
- easy to establish cause + effect
Weaknesses of Lab Experiment
- materials may lack mundane realism
- researchers cant be sure they are behaving naturally as there may be demand charcateristics
Strengths of Field Experiment
- higher mundane realism
- ps dont know they are being studied so no demand charcteristics
- real world study so more ecological validity and mundane realism
Weaknesses of Field Experiment
- may be time consuming and unpredictable
- less control over extraneous variables so hard to establish cause + effect
Strengths of Natural Experiment
- ps dont know they are being studied so no demand characteristics
- great for research that may be unethical to conduct
- its a real world study so more ecological validity and mundane realism
Weaknesses of Natural Experiment
- random allocation not possible, therefore there may be confounding variables that can threaten internal validity
- as we are not manipulating the IV it makes it hard to establish cause + effect
- less control over extraneous variables so hard to establish cause + effect
Strengths of Quasi Experiment
- allows comparison between types of people
- good control over IV and DV, so less extraneous variables
Weaknesses of Quasi Experiment
- random allocation not possible, therefore there may be confounding variables that can theaten internal validity
- low in ecological validity
- researchers cant be sure they are behaving naturally as there may be demand charcteristics
Strengths of Controlled Observations
- less risk of extraneous variables: increases ability to interpret findings
- richer and more complete info is obtained
Weaknesses of Controlled Observation
- artificial situations can influence behaviour
- artificially makes it hard to generalise findings: lacks ecological validity
- investigator effects + demand characteristics from ps knowing theyre being observed
Strengths of Naturalistic Observations
- removes problems from demand characteristics or evaluation apprehension
- provide richer + fuller info
- ecological validity
- may work better with children and animals
Weaknesses of Naturalistic Observations
- no control: extraneous variables
- often aware of observation
- problems of replication
- ethical issues if ps dont know behaviour is being observed
Strengths of Covert Observations
- reduces risk of altering behaviour: valid
Weaknesses of Covert Observations
- ethical problem of deceit
- doesnt allow observer to ask more qs
- observer cant take notes openly
Strengths of Overt Observations
- avoids ethical problem
- can ask more qs
- can take notes openly
- can use interview methods to check insights
Weaknesses of Overt Observations
- group may refuse researcher permission to observe: may prevent them from seeing everything
- hawthorne effect: behave differently, undermines validity
Strengths of Participant Observations
- high in ecological validity: real life settings
- long lasting: detailed + rich info
- in some its difficult for useful research to be carried out if havent joined group
- easy to interpret ps behaviour as developed deep understanding
Weaknesses of Participant Observations
- ethical problems: deceiving
- could change + distort behaviour of group members: investigator effects
- issues of accuracy + objectivity: write after, become involved: bias
Strengths of Non Participant Observations
- high ecological validity under naturalistic
- avoids investigator effects
- observations less distorted as researcher is detached
Weaknesses of Non Participant Observations
- harder to make detailed observations
- detachment makes it difficult to interpret behaviour
- ps may become suspicious
Strengths of Questionnaires
- cost effective: large amount of data collected quickly
- researcher doesnt need to be present
- may be willing to share more info
Weaknesses of Questionnaires
- social desirability bias: respondents may not be truthful: loss of validity
- can take a long time to design
- only a certain type may respond
- interpret qs in different ways
- cant clarify qs
Strengths of Unstructured Interviews
- more flexibility than a structured interview as interviewer can follow up points as they arise: richness of data increases validity
- easier to develop rapport
Weaknesses of Unstructed Interviews
- training needed
- analysis of results/data not simple and due to there being potentially so much info its hard to draw conclusions
- may be an element of social desirability bias
Strengths of Structured Interviews
- straightforward to replicate due to standardised format
- reduces differences between interviewers
- easy to compare
- fairly quick
Weaknesses of Structured Interviews
- not possible for interviewers to deviate off topic or explore interesting points
- stops interviewees from being able to elaborate which can be frustrating
- limits richness of data: can decrease validity
Strengths of Primary Data
- control the researcher has over data
- clearly fits aims and hypothesis of study
Weaknesses of Primary Data
- very lengthy and therefore expensive process: recruiting participants, conducting study, analysing data
Strengths of Secondary Data
- simpler and cheaper
- plays important role in psychological research including review studies, meta analyses and correlational studies
Weaknesses of Secondary Data
- variation in quality + accuracy of data: could be outdates or incomplete
- may not exactly match the researchers requirements
Strengths of Correlations
- can allow us to study naturally occuring variables
- can measure things we cant experimentally due to ethical issues
- can suggest patterns that then lead to experiments
Weaknesses of Correlations
- can tell us how variables are related but not why
- correlation doesnt equal causation (there is no cause and effect relationship as its not experimental)
- may overlook an important intervening variable
- bidirectional ambiguity: unclear which direction correlation is going in
Strengths of Mean
- it takes all scores into account so its the most sensitive measure
Weaknesses of Mean
- can give a peculiar measure that cannot represent reality
- easily distorted by extreme scores making it unrepresentative
Strengths of Median
- unaffected by extreme scores in one direction
- more representative than the mean, especially with small data sets
Weaknesses of Median
- less representative when the data set is polarised
Strengths of Mode
- most useful for large data sets
- unaffected by extreme scores
Weaknesses of Mode
- unreliable for use with small data sets as small changes to the scores can result in it being multi-modal
Strengths of Range
- useful when median is being used as an average as the range used the top and middle set and median is the middle number
- easy to calculate
Weaknesses of Range
- easily distorted by extreme scores
- only uses 2 numbers no matter how large data set is so its a really basic indication of how data is spread
- doesnt give an indication of spread of data scpres as it just looks at highest and lowest scores
Strengths of Standard Deviation
- uses all scores in data set for calculation so its a more precise measure of the spread of data
Weaknesses of Standard Deviation
- more difficult to calculate than range
- may hide some extreme scores within data set
Strengths of Case Studies
- gives very rich detailed info about the case
- can be used to investigate rare behaviours
- can be used to investigate behaviours that would be unethical to manipulate
- converging evidence: increases validity
Weaknesses of Case Studies
- each case unique so not generalisable
- may have to recall past (retrospective recall) which could be distorted
- researcher bias could be an issue if they are looking for a particular thing
Strengths of Peer Review
- peers should be experts in the field so we know that we can trust their judgement
- journals are international which means that there will be widespread dissemination of the new research among peers
- published research provides benefits for the unis the researchers work for
- peer review ensures that only the best research gets published
- anonymity allows peers to be honest
- publication in peer reviewed journals can enhance the reputation of researchers
Weaknesses of Peer Review
- it isnt always possible to find an appropriate expert to review a research proposal or report
- peer review results in a preference for research that goes with existing theory rather than dissenting or uncoventional research
- academic journals are expensive to buy
- anonymity may mean peers abuse their position
- journals may only want to publish positive results to increase the standing of the journal
Strengths of Content Analyses
- high ecological validity: content is part of evryday, not artificial
- replicable: anyone can access same media and apply same behavioural categories
- few ethical issues: isn’t any people in them as you’re observing the media
Weaknesses of Content Analyses
- investigator bias: bring own prejudices and preconceptions very easily especially when defining operationalised codes
- culture bias: content tends to come from one culture, isn’t representative
Strengths of Thematic Analyses
- flexibility: only notice themes as they emerge
- allows researchers own perspective: subjective nature
- few ethical issues: isn’t any people in them
Weaknesses of Thematic Analyses
- can’t use statistics: generates qualitative data
- subjectivity: may not spot themes they don’t personally relate to
