P2: Research Methods Flashcards
List and describe the key concepts of an investigation/study
- Aim: Statement of what research intends to investigate
- Hypothesis:Belief of what is true. Should be operationalised. 2 types.Directional/non-directional
- Experimental methods: Varies IV, records effect of IV on DV
Describe possible research issues that can appear in studies(list 3)
Extraneous/Confounding Variable:
-EV= nuisance variables. Don’t vary with IV
-CV=vary systematically with IV ∴ unknown if changes due to CV or IV
Demand Characteristics: Any cues that may reveal aim
Investigator Effects: Effect of investigator’s behaviour on outcome of research
Describe 4 possible research techniques
-Randomisation: Use of chance when designing studies
-Standardisation: Use of same formalised procedures
-Control group:(Baseline) setting purpose of comparison
-Single/double Blind:
Single= Participant unaware of aim
Double= Research/participant unaware of aim
Describe and Evaluate Independent groups
1 group= Condition A, 1 group= Condition B
Should be Randomly Allocated to experimental groups
+No order effects(of testing)
+Harder to guess aim(Less demand characteristics)
-Individual differences(different ppl act different)
-Double participants require (time/money)
Describe and Evaluate Repeated Measures
Same ppl participant in all conditions
Order of conditions should counter balance(avoid effect order)
+No Individual differences(Demand Characteristics)
+Fewer Participants(Money/time)
-Effect of order(Better 2nd time)
-Demand Characteristics (Guess aims=change behaviour)
Describe and Evaluate Matched Pairs
2 groups of ppl but are related. Paired via relevant participant variables
+Individual differences(Matched on variable)
+No effect order(no practice/fatigue)
-Matching ≠perfect(Time/ unable to control all Variables)
-More participants(time/money)
State all 4 types of experiments
- Laboratory
- Field
- Natural
- Quasi-experiment
Describe and Evaluate Laboratory experiment
Controlled environment: EV/CV regulated
IV manipulated, effects on DV recorded
+Internal Validity(EV/CV minimised)
+Easy Replication(Standardised procedure= retest able)
-Generalisation(Artificial/low ecological validity)
-Demand Characteristics(Know being studied)
Describe and Evaluate Field experiment
Natural. Researcher goes to participant
IV manipulated, effects on DV recorded
+Generalisation(comfort in own environment)
+Ecological Validity(Unaware of study=natural)
-CV uncontrollable(effect maybe due to CV not IV)
-Ethics(invasion of privacy, informed consent?)
Describe and Evaluate Natural experiment
IV would be varied even if researcher did nothing
DV maybe/measured naturally occurring.e.g.exam results
+Ethical(e.g.effects of institutionalisation force= bad)
+Ecological Validity(real-life issues/practical)
-Occurrence rate(many=one-offs ∴no generalising)
-No Random Allocation(effects maybe due to CV not IV)
Describe and Evaluate Quasi-experiment
IV based on pre-existing difference(e.g.age)No one manipulates it, it simply exists
Dv maybe/measured naturally occurring.e.g.exam results
+Often high control(shares strengths of lab studies)
+Comparisons available(e.g.Got autism or not)
-No Random Allocation(effects maybe due to CV not IV)
-Causal relations not demo(unsure if change in DV due to IV)
Describe all the elements involved in sampling:
- Population
- Sample
- Generalisation
- Bias
- Population: Large group of ppl that are being studied
- Sample: Small group from population, representing population
- Generalisation:Sample drawn= assumptions made of population
- Bias: certain groups maybe under/over represented
Describe and Evaluate Opportunity sampling
Consist off: Most available/easiest to obtain ppl
+Quick(convent ∵uses ppl closest to you)
-Biased(Unrepresentative of target population ∵ sample drawn from V specific street)
Describe and Evaluate Volunteer sampling
Consist off: Self-selection. Participants select themselves
+Ppl= willing(more motivation vs ppl on street)
-Biased(ppl may share certain traits.e.g.Keen/curious)
Describe and Evaluate Random Sampling
Consist off: Equal chance of selection from target population. Typically via lottery method
+Potentially Unbiased(free from researcher bias)
-Representation ≠ guaranteed(possible= biased sample)
Describe and Evaluate Systematic Sampling
Consist off: Ppl selected using a set pattern(sampling frame)
+Unbiased(Objective method)
-Time/effort(complete list of population required)
Describe and Evaluate Stratified Sampling
Consist off: Ppl selected via frequency in target population. Use of Strata(Sub-groups) identification
+Representative method(More generalisable vs others)
-Stratification≠perfect(cannot reflect all ways ppl differ)
Define Ethical issues
When conflict between rights of participant n aims of research occurs
Describe and explain ways of dealing with ethical issues
-INFORMED CONSENT: ppl should be able to make informed judgement about whether to take part
Presumptive=Ask similar group
Prior General=agree to be deceived
Retrospective=consent after study
-DECEPTION: Misleading/withholding info. Debrief should be provided at end including=
True aims, Other withheld info, how data will be used, Right to withhold data
-PROTECTION FROM HARM: Should be no more risk than everyday life= Right to withdraw at anytime, reassured behaviour was normal, provide counselling if needed
-PRIVACY/CONFIDENTIALITY: Right to control info= data should be protected, identify hidden, data not to be shared with others
Describe and Evaluate Correlations
ASSOCIATION: Strength/direction of a link between 2 co-variables
CORREALTION VS EXPERIMENT
-Experiment: Researcher manipulates IV records effect on DV
-Correlation: No manipulation ∴no cause/effect demo
(Influence of EV not controlled ∴maybe 3rd factor causing relation(Intervening Variable))
+Useful starting point(strong relation=future hypothesis)
+Economical(cheaper/less time-consuming VS Lab)
-No cause/effect(not always causal ∵ intervening V)
-Methodology flawed(measurement for 1 Variable could be inaccurate ∴ low validity)
Describe and evaluate Observational techniques
Observational TECH
+Capture unexpected behaviour
-Researcher bias
NATURALISTIC: normal places behaviour would occur
+Ecological Validity(∴ generalisable)
-Low Control(Uncontrolled EVs)
CONTROLLED: Some control/manipulation of Variables
+Replication(Standardised Procedures)
-Low Ecological Validity(Not natural)
COVERT: Unaware of study
+Demand Characteristics reduced(∴ better validity)
-Ethics(Invasion of privacy)
OVERT: Aware of study
+Ethics(Consent)
-Demand Characteristics(Not natural)
PARTICIPANT: Research joins group being studied
+Greater insight(∴ more validity)
-Loss of obj(too much identification= threats validity)
NON-PARTICIPANT:Researcher separates from study
+More objective(less chance of bias ∴ more validity)
-Loss of insight(maybe too removed ∴ low validity)
Describe and evaluate 3 observational designs
BEHAVIOURAL CATEGORIES:Target behaviour broken up into set observable categories(like.Operationalisation)
-Hard=unambiguous categ(hard to make not overlap)
-Dustbin categ(Dumped behaviours go unrecorded)
TIME SAMPLING: Observations made at regular intervals
+Less NO. Observations(More systematic/structured)
-Unrepresentative( May miss stuff)
EVENT SAMPLING: recored each time target behaviour occurs
+Record infrequent behaviour(Vs time sample, less missed)
-Complex behaviour simplified(too complex=unrecorded ∴ low validity)
Describe and Evaluate questionnaires as a self-report technique
Pre-set list of written questions/items which a participant responds to
+Cost-effective(large data gather quick)
+More willing to open up(less social desirability bias)
-Demand Characteristics(not honest= social desire bias)
-Response bias(may favour a response(all agree))
Describe and Evaluate the different interviews styles as a self-report technique
STRUCTURED INTERVIEW:Pre-determined list of questions asked in a fixed order
+Replication(Standardise format)
-Cannot elaborate(no deviation from topic)
UNSTRUCTURED INTERVIEW:Free-flowing about general topic, encouraged to elaborate
+Flexibility(more insight into their view)
-Difficult to replicate(Risk interviewer bias)
SEMI-STRUCTURE INTERVIEW: List of questions worked out in advance, free to ask follow-up questions when appropriate.
Describe and explain what makes a good questionnaire
-Avoid Jargon
-Avoid Double-Barrelled Q(2Qs in 1)
-Avoid Leading Q
CLOSED Q: Limited choices(Quantitative data)
+Easier to analyse(can make graphs)
-Restriction(lack of representation= low validity)
OPEN Q: Provide own answers(Qualitative data)
+No restriction(Detailed=accurate)
-Hard to analyse(maybe forced to reduce data to stats)
Describe and explain what makes a good interview
- Interview schedule: Standardised list of Q to cover
- Quiet Room: More likely to open up
- Rapport: Begin with neutral Q= relax participant
- Ethics: Reminders= ANS will be treated in confidence
Describe a Pilot Studies
Used in all types of research
-Trial Run: small scale trial run done before hand to determine any errors ∴ you can fix before the real thing ∴ save money/time
Describe and Evaluate the differences between Quantitative and Qualitative data
Quantitative: Numerical data \+Easy to analyse(make graphs) -Oversimplifies(Individual meanings lost) Qualitative: non-numerical data \+Represents complexities(Detailed) -Hard to analyse(hard to summarise)
Describe and Evaluate Primary, Secondary and Meta data/analysis
Primary: First hand collect data for study
+Bespoke(all relevant data)
-Time/effort(money)
Secondary: Collected by someone else conducting same study
+Cheap(save money/time)
-Quality control(outdated/incomplete)
Meta-Analysis: Combing data from large NO. of studies
+Good Validity(large sample=generalisable)
-Publication bias(researcher may not select all relevant studies)
Describe and Evaluate the 3 measures of central tendency
MEAN: Arithmetic Average \+Sensitive -Unrepresentative(outliers=distorted) MEDIAN: Middle Value \+outlier proof -Less sensitive MODE: Most Frequent Value \+Relavent to categorical data -too simple
Describe and Evaluate the 2 measures of dispersion
Range: difference of biggest/lowest (+1)
+Easy to do
-Do account of distribution between scores
Standard Deviation: AVG spread around mean
+More precise
-Misleading(hides outliers)
Assess the Sign test
USE CONDITION: Analyse difference between scores
for NOMINAL DATA
METHOD: Scores for test B - test A = tally total of +/-.
-Neutral(e.g.5-5=0)= ignore
TALLY up frequency of both signs
-‘S’ VALUE = total of less frequent sign
If S is equal to/less than CV ∴ S is significant/ experimental hypothesis is retained
Describe and Evaluate Peer reviews
Before publication, all aspects investigated by peers.
AIM: validate/suggest improvements/funding
+Protects quality(minimises fraudulent research)
-Used to critics rivals(∵lack of funding=fight)
-Publication bias(Need 4 eye-catchy=remove things)
-Ground-breaking study=buried(more critical of studies which contradicts their views)
Explain what Correlation Coefficient is
Represents strength of correlation(+1 or -1)
Close to 1= strong, 0= none, +=pos,-=neg
SIgn= direction of correlation
e.g. +1 = perfect positive
Describe and Evaluate Case Studies
Longitudinal.Can involve gathering data from friends/family.
Often involve unusual individuals/events.
Can involve concentrating on typical cases.e.g.old guy recalls childhood.
DATA collection: Interviews/observations/questionnaires
(QUALITATIVE)/Psychological tests(QUANTITATIVE)
+Detailed(= more validity)
+Enables study of rare behaviour(e.g. HM)
-Researcher bias(conclusion subjective)
-Participants accounts biased(prone to memory decay)
Describe and Evaluate Content Analysis
Indirect study via communications(observational research)e.g. spoken interactions, written forms,examples from media
Coding first stage .e.g.counting NO. of times word x appears (QUANTITATIVE DATA)
Thematic analysis .e.g.mental health theme reoccurring.
(QUALITATIVE DATA)
+Ethic(material=public usually(TVS) ∴no consent issue)
+Flexible(can produce QUANTITATIVE/QUALITATIVE)
-Communications outta context(may add motivations not intended ∴reduce validity of conclusions
-Lack Objectivity(bias(specifically descriptive ∴ validity affected)
Describe and Evaluate reliability across all methods of investigation
RELIABILITY
(replication with same results) = consistency
ASSESSING RELIABILITY
-Retest: test same person twice
-Inter-observer: Compares different observers watching same observation
-Correlation: coefficient should be above +.80=reliable
IMPROVING RELIABILITY
-Questionnaires: rewrite Questions(e.g.less ambiguous)
-Interviews: improve training(no leading Q) + use same interviewer
-Standardised Procedures: good control of aspects
-Observations: operationalisation of behavioural categories(shouldn’t be overlapping)
Describe and Evaluate types of validity across all methods of investigation
TYPES OF VALIDITY = is the result legitimate(of the IRL world)
Data can be reliable but not valid(e.g.IQ test)
Ecological Validity: If findings generalise to other settings
Temporal Validity: Do findings remain true over time
ASSESSING VALIDITY
Face Validity(eyeballing): Does test look like it measures what it should
Concurrent Validity: Whether findings= similar to (older)well-established test(correlation should exceed +.80 for validity)
IMPROVING VALIDITY
-Control groups: allows comparisons ∴ more confident changes in DV due to IV
-Questionnaire: lie scale= controls for effects of social desirability bias (assured of confidentiality)
-Observation: Categories. Well-defined, operationalised, not overlapping
-Qualitative research: Triangulation= using NO. of different sources
Describe Statistical testing
-Purpose: to test if results are due to chance
3 CRITERIA FOR CHOOSING STATS TEST:
1) Looking for Difference/Correlation
2) Experimental design related(Repeated/matched pairs)/unrelated(Independent group?)
3) LV of measurement
CONDITIONS FOR STATISTICAL TESTS
-Nominal data: (Categories) No order, only appear in 1 category
-Ordinal data: (Ordered, subjective intervals)
Based on subjective opinion VS objective measure.e.g.Rate how much you like x on scale of 1-10
-Internal data: (Units of equal size, based on numerical scales)
Describe Probability and Significance
Null Hypothesis= no difference/correlation. If stat test is not significant the null hypothesis is accepted.
0=statistical impossibility, 1= statistical certainty
USING STATISTICAL TESTS
Usual Lv of significance=/less than 0.05(5%)
Check for statistical significance. Calculated V compared with CV.
-To find CV: 1)find if hypothesis is one-tailed/two-tailed
2)(N)No. ppl, or degree of freedom(df)
3)Lv of significance (p value)
TYPE I/TYPE II ERROR
-Type I error: Null rejected, when null= true
Optimistic error= sig difference found when 1 doesn’t exist.
Likely = if sig Lv is too lenient
-Type II error: Null accepted, when ALT = true
Pessimistic error
Likely = if sig Lv is too stringent
Describe and Evaluate Reporting psychological investigation
- Abstract: Summary of the study with all major elements
- Introduction: Literature review. look at relevant theories, concepts, studies (that are relevant)
- Method:State. Design, Sample, Apparatus/materials, Procedure, Ethics(∴ others can replicate study)
- Results: Descriptive(graphs, charts),Inferential(reference of stat test). raw data collected appear in appendix.
- Discussion: Summary(findings), relations (comparison research), consideration of limitations/weakness, IRL implications
- Referencing: Sources.e.g.journal articles, books, websites
Describe and Evaluate the 6 Features of Science
PARADIGMS/PARADIGM SHIFTS
Paradigm(scientific disciplines)= shared set of assumptions/methods.
Paradigm shifts(scientific revolution):ppl start accept paradigm ∵ too much contradictory evidence to ignore
THEORY CONSTRUCTION
set of general laws= explain particular events
Make clear predictions based on theory.
Hypothesis tested ∴determine support/refused
Deduction: deriving new hypothesis from existing theory
FALSIFIABILITY
Proof impossible.
Real theories =challengeable= prove false/not
Pseudoscience = cannot be challenged ∴ not proved false yet
REPLICABILITY
Theory=trustable= replicable = extend to which we can generalise
OBJECTIVITY
researcher must keep critical distance = reduce bias
EMPIRICAL METHOD
Direct experience= importance of data collection via direct sensory experience.e.g.observational/experimental methods(overt/repeated G)
