Research Methods Flashcards
Operationalise meaning
Ensuring that variables are in a form that can easily be tested
Standardised procedures
A set of procedures that are the same for all participants in order to be able to repeat the study
Repeated measures limitations
ORDER EFFECT —>
Practice effect - do better on the second test
Boredom effect - do worse on the second test due to boredom
GUESS CAUSE- on the second test participants may guess the purpose of experiment, change behaviour
Repeated measures dealing with limitations
PRACTICE EFFECT - use two different tests - though the two tests must be equivalent
ORDER EFFECTS - counterbalancing (reversing the order)
GEUSS THE AIM- cover story about aim used
Independent groups limitations
Participant variables - act as a confounding variables
Need more participants
Independent groups dealing with
Randomly allocate participants to deal with personal differences
Matched pairs issues
Time consuming
Cannot control all participant variables as only match on variables KNOWN to be relevant
Matched pairs dealing with
Restrict no. Of variables to match
Conduct a pilot study to identify all key variables
Lab experiment limitations
IV/DV may be operationalised in a way that doesn’t represent every day experiences( lacks mundane realism) - leads to low ecological validity
Field experiment strengths
Participants likely to be unaware - no demand characteristics
In natural environment -> more relaxed
Natural experiment
When it is not possible (ethically or practically) to deliberately manipulate an IV - it varies ‘naturally’
Quasi experiment
IV is too naturally occurring. Has not been made to vary by anyone however, it simply exists (gender)
Quasi experiment STRENGTHS and WEAKNESSES
STRENGTHS - allows comparisons between types of ppl
WEAKNESSES - participants may be aware of being studied - demand characteristics/reduced internal validity
- dependant variable may be artificial task-reduces mundane realism
Investigator effects
Any cues from an investigator that might encourage behaviours in the participant and which lead to the fulfilment of the investigators expectations
SONGLE BLIND DESIGN
DOUBLE BLIND DESIGN
EXPERIEMENTAL REALISM
SBD- participant not aware of aims and/or conditions they will receive - stops them seeking cues
DBD- participant and experimenter blind to aims/hypothesis. Less likely to give or receive cues
ER- task sufficiently engaging that participant only pays attention to task
Stratified sample
Subgroups within a population are identified. Participants are obtained from each group in accordance to their groups proportion in the population
Systematic sampling
Using a predetermined system to select participants such as the nth. Person in a phone book.
Opportunity sampling STRENGTHS AND WEAKNESSES
STRENGTHS - easy and quick
LIMITS - inevitably bias as sample drawn from a small proportion of population
Random sampling Strengths and weaknesses
STRENGTHS - unbiased - equal chance of selection
WEAKNESSES - time consuming - need every member of population included
Stratified sampling strengths and weaknesses
Strengths - most representative as is proportional as randomly selected
Weaknesses- very time consuming to identify subgroups and randomly select
Systematic sampling STRENGTHS WEAKNESSES
STRENGTHS- unbiased
Weaknesses- no truly unbiased/random unless you start by selecting a number using a random method and then do this method afterwards
Volunteer sampling STRENGTHS WEAKNESSES
STRENGTHS- give access to variety of participants making sample more representative and less biased
WEAKNESSES- biased as participants may be more motivated and/or with extra time on their hands. Leads to volunteer bias
Ethical issues
Informed consent
Deception (cannot deliberately give false information)
Right to withdraw
Protection from physical and psychological harm
Confidentiality
Privacy
Dealing with ethical issues
Ethical guidelines (BPS ethical guidelines)
Cost benefit analysis
Ethics committees
Punishment (barred from psychological practice)
Naturalistic observation
Situation where everything has been left as it normally is - researcher does not interphere
Controlled observation
Some variables in environment are regulated - participants more likely to know they are being studied
Overt observation
Aware of observation
Covert observation
Not aware of observation
Non participant observation
Observer merely watching
Participant observations
Observer participating
Unstructured observations
Researcher records all relevant behaviour- no system
ISSUE - too much to record, most behaviour caught would be most eye catching (may not be relevant)
Structured observations
Observational techniques are objective and rigorous
Two types: behavioural categories, sampling procedures
Behavioural catagories
Breaking down actions into specific observation groups (I.e different facial expressions)
Sampling procedures
EVENT SAMPLING - counting no. Of times certain behaviour occurs
TIME SAMPLING - recording behaviours in a given time frame
STRENGTHS WEAKNESSES questionnaires
STRENGTHS- can be distributed to large no. Cheaply and quickly
- more willing to give personal information that in an interview (less self conscious
LIMITATIONS- biased towards ppl who can read/write and have time
Structured interview
Pre determined questions
Questioned in real time
Unstructured interview
New questions are developed over the course of the interview
Interview begins with general aims
Structured interview STRENGTHS WEAKNESSES
STRENGTHS- easily repeated - answers from different ppl can be compared
Easier to analyse that unstructured, as answers more predictable
WEAKNESSES- interviewers expectations may influence the answers the interviewees gives
- compatibility may be difficult if interviewer behaved differently
Unstructured intervention STRENGTHS WEAKNESSES
STRENGTHS - more detailed information obtained
LIMITATIONS- interviewers require more skill to develop questions on the spot - these ppl are more expensive
- questions may lack objectivity than the predetermined as they have no time to reflect on what to say
Questionnaire construction
- clarity
- bias
- analysis (closed questions)
- filler questions (distraction)
- sequencing (easy to hard questions)
- pilot study
Correlations
STRENGTHS WEAKNESSES
STRENGTHS- investigate trends in data. If correlation significant, further investigation justified
-easily repeated
WEAKNESSES- cannot assume causal conclusions, only correlations conclusions
- intervening variables may be the cause for the trend in data, and connect the co variables that are studies
Content analysis
Observational study where behaviour is observed indirectly in written/verbal material such as interviews, conversations, books, dairies or TV programmes
Meta analysis STRENGTHS WEAKNESSES
STRENGTHS- reviewing results from multiple studies increase validity of conclusions drawn
-often a group of studies on a similar topic have different results. Can reach an overall conclusion using MA
LIMITATIONS - research designs may vary between studies, so the studies are no longer truly comparable
Content analysis STRENGTHS WEAKNESSES
STRENGTHS- based in observations - high ecological validity
- when sources can be accessed by others, findings can be replicated
WEAKNESSES- observer bias reduces objectivity/validity because different observers may interpret observations differently
Case study WEAKNESSES STRENGTHS
STRENGTHS - rich in-depth data
- useful in researching human behaviour that is rare
WEAKNESSES- difficult to generalise from individual cases
- often use recollection of past event - may be unreliable data
- case studies are only identified after an event has occurred - cannot be sure changes were not already present
Measures of central tendency
Mean median mode
Measures of dispersion
Range standard deviation
Nominal data
Data in separate categories (I.e fave footie teams)
Ordinal data
Data ordered in a specific way. Intervals between data not the same. (I.e orders in how much they like their fave footie teams)
Interval data
Data measured using units of equal intervals ( I.e counting no. Of correct answers)
Standard deviation
Measure of the average distance between each data item above and below the mean, ignoring plus or minus values
Standard deviation STRENGTHS WEAKNESSES
STRENGTHS - is a precise measure of dispersion because it takes all the exact values into account
WEAKNESSES- may hide some characteristics of the data set
Histogram
Areas within the bar chart must be proportional to the frequencies represented. No gaps between bars
Quantitive v qualitative data
Quantitive - how much or how long, how many etc. (Numbers)
Qualitative - Can’t be counted but can be put into categories then counted . What ppl think/feel (words)
Primary v secondary data
Primary - data observed/collected from first hand experience . Can be collected using an experiment
secondary - information that was collected for a purpose other than the current one (I.e data collected for a different study, government statistics)
One tailed v two tailed
One tailed- directional hypothesis - know which direction experiment going
Two tailed - non directional hypothesis - experiment goes in both ways
