Research Methods Flashcards
DV
Variable we measure
IV
Variable we manipulate
Operationalisation
Define variables specifying set of operations/behaviour measured or manipulated
Hypothesis
Precise and testable statement (prediction)
Aim
Investigator intends to find out in study
Standardise procedures
Procedure same for all pps and can be repeated
EV
Difficult to detect significant effect on DV
Directional hypothesis
State difference of the condition/groups of study
People who do HW with tv on WILL PRODUCE worse results than those who have it off
Non directional hypothesis
Simply state there is a difference between 2 conditions/groups
People who do HW with the tv on PRODUCE DIFFERENT results than one with it off
Confounding variables
Varies systematically with IV and changed DV effect the cause and effect relationship
pps variables
Characteristics of the pp effect the DV e.g motivation gender experience
Situational variables
Research influence pps behaviour e.g order effects
Mundane realism
Study mirror the real world
Generalisation
Apply result beyond research and results e.g setting group
Validity
True/legitimate explanation
Internal validity
Control and realism within study itself
IV DV EV CV
External validity
Generalisability beyond study
Ecological validity
Generalise to other situations
Population validity
Don’t generalise to other people
Historical validity
Can’t generalise time period
Demand characteristics
Pps unconsciously given cues help work out aim lead to screw you effect internal validity lowerd
Investigators effects (bias)
Anything investigator does to effect study wasn’t intended e.g interfering with pps
Single blind design
Pps unaware of aim
Double blond design
Experiment and pps unaware of aim unable to give away cues
Lab experiments
Investigate the cause and effect in controlled environment
Strengths of lab experiments
Well controlled minimise Ev increase internal validity
Easily replicated cuz of standardised procedures
Weaknesses of lab experiments
Artificial situation lack mundane realism
Won’t behave naturally - demand characteristics lower ecological validity
Filed experiment
Iv is manipulated in a natural setting
Strengths of field experiment
Less artificial increases mundane realism increase ecological validity
Unaware they in experiment lower demand characteristics
Weaknesses of filed experiments
Less control of ev and cv reduce internal validity
Time consuming/expensive
Can’t be easily replicated lower external validity
Natural experiment
Iv can’t be manipulated directly
Strengths of natural experiment
Allow research iv not manipulated for ethical or practical reasons
Mundane realism increase internal validly
Weakness of natural experiment
Can’t demonstrate casual relationship as Iv not directly manipulated
Quasi experiment
Iv is the characteristic of the pps e.g gender or age
Strengths of quasi experiment
All comparisons with different types of people
Weakness of quasi experiment
Can’t demonstrate casual relationship between Iv because not directly manipulated
Random allocation not possible can’t control cv lower internal validity
Repeated measures design
Take part all condition of study
Independent groups
Take part in 1 condition of the study
Matched pairs
Pps paired from each condition based on variable e.g iq memory ability
Compare pair performance
Weakness of repeated measures
Order effect e.g bordom and practice
Demand characteristics guess aim
Improve repeated measures
Counter balancing
Use a different test but match difficulty
Weakness Independent groups
Participant variables
More pps needed
Improve independent groups
Randomly allocate
Reduce pps variables
Weakness Matched pairs
Time consuming
Can’t control all variables
Improve matched pairs
Pilot study
Restrict number of variables make easier
Counter balancing
Pps take part in condition a and b reffered as abba
Attempt to balance out order effects between 2 conditions
Experimental realism
More artificial task engage keep attention on task than the observation
Randomisation
Use of chance where possible reduce influence on aim and control investigator bias
Random allocation
Technique to choose pps for treatment group and control group
Standardisation
All pps subjet to same environment and procedure minimes Ev
Random sample
Equal change being chosen
Names in a hair chosen out lottery method
Strength of random sample
Free from researcher bias no influence on selection
Weakness of random sample
Time consuming can be unrepresentative
Systematic sample
Nth target pop is selected e.g every 3rd house on each street
Produces a Sampling frame
Strength if systematic sample
Avoid researcher bias no influence who get picked fairly repesentive
Weakness systematic sampling
Time consuming
Stratified sampling
researchers divide subjects into subgroups called strata based on characteristics that they share
Strength of stratified sampling
Avoid researcher bias
Representive reflect composition of population
Weakness of stratified sampling
Stratification not perfect can’t reflect all ways people are different
Opportunity sampling
Select anyone willing available
Strength of opportunity sampling
Convenient
Less costly
Weaknesses of opportunity sampling
Unrepresentative only specific area can’t generalise
Researcher has Control over selection could be bias
Volunteer sampling
People select themselves on news papers hand outs Notice boards
Weakness of volenteer sample
Select themselves could be similar types of people can’t generalise
Ethical issues
Conflict between what researcher need to do to produce useful research and the pps rights
Informed consent
Should no the aim and what they are taking part in won’t be natural behaviour
Deception
Deliberately misleading/withholding info said to be not given inform consent
Jusified if pp not caused harm
Protection from harm
Pps not put ant any more risk than day to day living physical and psychological harm e.g embarrassment stress
Privacy and confidentiality
Right or privercy - Control personal info about themselves
Confidently- right by the law data protection act
5 ethical issues
Inform consent
Right to withdraw
Pricey and confidentiality
Protection from harm
Deception
Non pps observation
Only watches does not interact with pp
Pps observation
Part of group being watched unknown to pps
Overt observation
People no being watched
Covert
Unknown being watched may be informed after
Controlled
Some variables regulated by researcher e.g naturalness of situation and behaviour
Naturalistic
Behaviour studied natural situation no interference from researcher
Strength of pp observation
Special insight into behaviour of group
Strength of non pp observation
Be objective not part of group being observed
Weakness non pp observation
Not understand type of behaviour
Overt strength
Less ethical issues
Overt weakness
Change natural behaviour
Covert strength
More natural
Covert weakness
Ethical issues
Strength of naturalistic observation
Realistic spontaneous behaviour high ecological validity
Weakness of naturalistic observation
Can’t control all variables
Controlled observation strength
Sharper foucous on all aspect of behaviour
Weakness of controlled observation
Less natural lack validity
Questionnaires
Set of written questions understand people think and feel about topic used DV In experiments
Open questions
Don’t have set of pre questions answer whatever they wish
Closed question
Fixed number of responses eg multiple choice rate scale
Improve questionnaire
Filler question- avoid finding out aim
Pilot study - small group questions refined
Sequence of sentences - easy then hard
Quantative
Numerically
Qualative
Words
One tailed test
Performed when hypothesis is directional
Two tailed test
Performed when hypothesis non directional
Calculated value
Work out yourself using statistical tests
Critical value
Compared with calculated value
Probability
Result down to chance
Lest 95% confident (0.05)
Iv effect dv
Significance
95% sure change in dv manipulation of Iv
Compare critical and calculated value
Probability recorded
P=0.05 or p<0.05 it’s 5% or less
Type 1 error
Accepting hypothesis you should reject
Flase +
To linent
Type 2 error
Rejecting hypothesis you should accept
False -
To hard
Nominal data
Consit of the number of pp falling into categories
Ordinal data
Placed in rank order
Interval data
Fixed intervals unit of measurement fixed throughout the range
Standard deviation
Spread of data around the mean
Strength of standard deviation
Precises measurment of dispersion exact measure take into account
Deprative statistics
Table graphs show frequencies measure central tendency dispersion
Inferential statistical
Test reported included calculated values/ significance levee
