Research Methods Summary

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Scientific Method

Major features of science:

  • Empiricism
  • Control
  • Objectivity
  • Theory
  • Replicability
  • Construction
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Scientific Method

Scientific Process:

  • Induction: Reasoning from particular to general
  • Deduction: Reasoning from general to particular 


  • Scientific Research is Desirable
  • Psychology shares to goals of science
  • Kuhn - no single paradigm
  • Lack of objectivity and control leads to experimenter bias and demand characteristics

Are goals of science appropriate?

  • Nomothetic vs Idiographic
  • Qualitative research - triangulation 
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Scientific Method


  • Reductionist - reduces complex phenomena to simple ones
  • Deterministic - searches for casual relationships 
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Validating Knowledge

Peer Review:

Serves three main purposes:

  • Allocation of research funding
  • Publication of scientific journals
  • Research assessment exercise 
  • Research published on the Internet requires new solutions 


  • May be an unachievable ideal
  • Anonmity allows honesty and objectivity
  • Publication bias favours positive results
  • May lead to presevation of the status quo 
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Validating Knowledge

Conventions of Scientific Reporting:

  • Abstract - summary of study
  • Introduction/aim - literature review and research intentions
  • Method - procedures and design of study
  • Results - descriptive and inferential statistics
  • Discussion - outcomes and implications of study
  • References 


  • Some changes in science are not logical changes but represent a shift in perspective
  • Burt research - an example of scientific fraud 
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Research Methods


  • IV varied to see effect on DV
  • Laboratory experiment - high on internal validity, low on external validity
  • Field experiment - more natural environment but more issues of control than lab experiment
  • Natural experiment - uses naturally occuring IVs but cannot conclude causality
  • Experimental designs - repeated measures, independent groups, matched pairs 

Self-Report Methods:

  • Questionnaires and Interviews
  • Structured - more easy to repeated
  • Unstructured - questions that evolve are dependent on answers given
  • May involve open or closed questions
  • Main problem = social desirability bias 
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Research Methods

Observational Studies:

  • Observing behaviour through behavioural categories 
  • Sampling methods - time and event sampling
  • Open to subjective bias - observations affected by expectations 

Correlational Analysis:

  • Concerned with relationship between two variables
  • Does not demonstrate casuality 
  • Other variables may influence any measured relationship 

Case Studies:

  • Detailed study of individual, institution or event
  • Generally longitudinal, following group or individual over a long period of time
  • Allows study of complex interaction of many variables
  • Difficult to generalise from specific cases 
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Design Issues


  • Experimental Research - allows for replication of study
  • Observations - inter-obsever reliability can be improved through training
  • Self-report - internal reliability and external reliability 


  • Internal validity - test what we intended to test?
  • External validity - can results be generalised?
  • Lab experiments not necessarily low in external validity
  • If low in mundane realism, reduces generalisability of findings
  • Observations = internal validity affected by observer bias
  • Self-report techniques = face and concurrent validity 
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Design Issues

Sampling Techniques:

  • Opportunity - most easily avaliable participants
  • Volunteer - through advet but subject to bias
  • Random - all members of target population must be equal chance of selection 
  • Stratified and quota - different subgroups with sample, leads to more representative 
  • Snowball - researcher directed to other similar potential participants 
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Ethical issues with Humans:

  • Informed consent and deception
  • Harm - what is too much?

Code of Conduct:

  • Respect for worth and dignity of participants
  • Right to privacy, confidentiality, informed consent and right to withdraw
  • Intentional deception only acceptable in some circumstances
  • Competence - retaining high standards
  • Protection from harm and debriefing 
  • Integrity - being honest and accurate in reporting
  • Use of ethical guidelines in conjunction with ethical committees
  • Socially sensitive research - potential social consequences for participants 
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Ethical Issues with non-Humans:

  • Reasons for animal use - offers opportunity for greater control and objectivity
  • Moral issues - sentience (experience of pain/emotion)
  • Specieism - form of discrimination against non-human animals
  • Animal rights - Regan (1984), no animal research is acceptable
  • Do animals have right if they have no responsibilities?
  • Animal research subject to strict legislation (Animals Act; BPS guidelines)
  • The 3 R's - reduction, replacement, refinement 
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Probability and Significance

  • Probability = likelihood that a pattern of results could arise by chance
  • If probability extremely unlikely, then result is statistically significant 
  • Inferential tests determine whether chance or real trend in data
  • Probability levels represent acceptable level of risk of making a type 1 error
  • More important research, more stringent significance levels
  • Type 1 error = null hypothesis is rejected when true
  • Type 2 error = null hypothesis is accepted when false 

Inferential Tests 

  • Different research designs require different tests
  • Different tests for different levels of measurement (nominal, ordinal, interval, ratio)
  • Tests yield observed values, and then compared to CV to determine significance level
  • One tailed = directional
  • Two tailed = non-directional
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Inferential Tests

Spearman's Rho: 

  • Ordinal data
  • Predicts correlation between two variables
  • Each person is measured on both variables 


  • Nominal
  • Predicts differences between two conditions between two variables
  • Data is independent
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Inferential Tests

Mann-Whitney U

  • Predicts diffeence between two sets of data
  • Independent groups design
  • Ordinal


  • Difference between two sets of data
  • Repeated designs or matched pairs
  • Data at least ordinal 
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Descriptive Statistics

Central Tendancy:

  • Indicates typical or 'average' score
  • Mean = sum of all scores divided by number of scores
  • Median = middle value in ordered list of scores
  • Mode = most common value 

Measures of Dispersion:

  • Indicate spread of scores
  • Range = difference between highest and lowest score
  • Standard deviation = spread of data around mean


  • Bar chart = illustration of frequency, height of bar represents frequency
  • Scattergram = illustration of correlation, suitable for correlational data 
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Qualitative Data

Key points:

  • Quantitative = not relevant to 'real life'
  • Qualitative represents world as seen by individual
  • Emphasises collection of subjective information from participant
  • Data sets tend to be large
  • Qualitative data cannot be reduced to numbers
  • Can be examined for themes 


  • Coding using top-down approach (thematic analysis) = codes represent ideas/themes from existing theory
  • Coding using bottom-up approach (grounded theory) = codes emerge from data
  • Behavioural categories used to summarise data
  • Reflexivity indicates attitudes and biases of researcher
  • Validity demonstrated by triagnulation
  • Reliability checked by inter-rater reliability 
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