Research Methods

  • Created by: ash8642
  • Created on: 21-04-19 20:35

Experimental Method

Experimental Method

  • Aims - the purpose of the investigation
  • Hypothese - the formulation of a testable statement
  • Directional or non-directional - identifying a difference/correlation or not; one-tailed and two-tailed predictions

Variables

  • IVs and DVs - IV is manipulated, DV is measured 
  • Levels of the IV - experimental and control conditions
  • Operationalisation - 'de-fuzzying' variables
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Control of Variables

  • Extraneous variables - nuisance variables but randomly distributed
  • Confounding variables - vary systematically with the IV
  • Demand characteristics - participants second guess the aims and alter their behaviour
  • Investigator effects - unconscious influence of the researcher on the research situation
  • Randomisation - use of chance to reduce the researcher's influence
  • Standardisation - ensuring all participants are subject to the same experience
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Experimental Design

Type of Design

  • Independent groups - participants in each condition of an experiment are different
  • Repeated measures - all participants take part in all conditions
  • Matched pairs - similar participants are put in pairs and allocated different experimental conditions

Evaluation

  • Independent groups
    • Less economical, no order effects, participant variables not controlled
  • Repeated measures
    • Order effects, demand characteristics, no participant variable problems, more economical
  • Matched pairs
    • No order effects, cannot match participants exactly, time-consuming
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Types of Experiments

Types of Experiments

  • Lab - IV is maniplulated in a controlled setting
  • Field - IV is manipulated in a natural setting
  • Natural - IV has been manipulated naturally, effect on DV is recorded
  • Quasi - IV based on existing difference between people, effect on DV is recorded

Evaluation

  • Lab - high internal validity, low external validity, casue + effect, replication, demand characteristics
  • Field - lower internal validity, higher external validity, ethical issues
  • Natural - low internal validity, high external validity, unique research, opportunities may be rare
  • Quasi - low internal validity, high external validity
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Sampling

Populations and Sampling

  • Random - all memebers of the population have an equal chance of selection
  • Systematic - selecting every nth person from a sampling frame
  • Stratified - sample reflects the proportions of people within different population strata
  • Opportunity - choosing whoever is available
  • Volunteer - participants 'self-select'

Evaluation

  • Random - no researcher bias, time-consuming, may end up with biased sample
  • Systematic - no researcher bias, usually fairly representative, may end up with biased sample
  • Stratified - no researcher bias, representative, cannot account for all sub-groups
  • Opportunity - convenient, researcher bias, unrepresentative
  • Volunteer - less time-consuming, attracts a certain profile of person
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Ethical Issues

Ethical Issues

  • Informed consent - advising participants of what is involved; may reveal research aims
  • Deception - telling the truth
  • Protection from harm - minimising psychological and physical risk
  • Privacy and confidentiality - protecting personal data

Evaluation

  • Informed consent
    • Get permission, presumptive/prior general/retrospective consent
  • Deception/protection from harm
    • Debriefing
  • Privacy and confidentiality
    • Maintaining anonymity, use numbers not names
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Observational Techniques

Types of Observations

  • Naturalistic - behaviour observed where it would normally occur; no control over variables
  • Controlled - some control over environment, including manipulation of variables to observe effects
  • Covert + overt - observing participants with or without their knowledge
  • Participant + non-participant - to join the group or remain an outsider

Evaluation

  • Naturalistic - low internal validity, high external validity
  • Controlled - low internal validity, high external validity
  • Covert + overt - Covert: low participant reactivity, ethically questionable; Overt: behaviour may be affected
  • Participant + non-participant - Participant: increased external validity, may 'go native'; Non-participant: more objectivity
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Pilot Studies

Research Techniques

  • Pilot studies - checking procedures and materials; making modifications
  • Single blind - participants aren't made aware of research aims until the end
  • Double blind - neither participants nor the individuals conducting the research know the aim beforehand
  • Controlled group/condition - used as a comparison
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Observational Design

Designing Observations

  • Unstructured/structured - researcher records everything (unstructured) or controls what is recorded (structured)
  • Behavioural categories - target behaviours broken down into observable components
  • Sampling methods - continuous; event sampling; time sampling

Evaluation

  • Unstructured/structured
    • Unstructured: more information but may be too much, qualitative data harder to analyse; Structured: may miss behaviours
  • Behavioural categories
    • Must be observable, avoid dustbin category, no overlap
  • Sampling methods
    • Event: useful for infrequent behaviour, may miss complexity; Time: less effort but may not represent whole behaviour
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Self-Report Techniques

Questionnaires

  • Pre-set list of written questions
  • Closed/open questions - fixed number of answers or not

Evaluation

  • Questionnaires
    • Can distribute to many people
    • Easy to analyse
    • Social desirability bias
    • Acquiescence bias
  • Closed/open questions
    • Produces qualititative or quantitative data
    • Affected ease of analysis
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Self-Report Techniques

Interviews

  • Structured - pre-set questions in a fixed order
  • Unstructured - no set formula, just a general topic; questions developed based on responses
  • Semi-structured - pre-set questions with flexibility to ask follow-ups

Evaluation

  • Structured
    • Similar to questionnaires but fewer respondents
  • Unstructured
    • More flexibility
    • Analysis more difficult
    • Social desirability bias may be reduced by rapport
  • Semi-structured
    • Advantages of both structured and unstructured
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Self-Report Design

Designing Self-Report

  • Questionnaires - Likert scale, rating scale, fixed choice option
  • Interviews - standardised interview schedule to avoid interviewer bias; awareness of ethical issues

Writing Good Questions

  • Overuse of jargon - don't be too technical
  • Emotive language and leading questions - replace 'loaded' words and phrases with neutral ones
  • Double-barrelled questions and double negatives - ask one question only in a clear way
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Correlations

Correlations

  • Types of correlation - positive, negative, and zero/null
  • No IV or DV
  • No manipulation of variables

Evaluation

  • Strengths
    • Useful premliminary tool
    • Quick and economical to carry out, using secondary data
  • Limitations
    • Cannot demonstrate cause and effect
    • Third variable problem (intervening variable)
    • Misuse and misinterpretation
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Data Analysis: Kinds of Data

Qualitative and Quantitative

  • Qualitiative - written, non-numerical description of the participants' thoughts, feelings, opinions
  • Quantitative - expressed numerically rather than in words

Evaluation

  • Qualitative
    • Rich in detail
    • Greater external validity
    • Difficult to analyse
    • Conclusions may be subjective
  • Quantitative
    • Easy to analyse
    • Less biased
    • Narrow in scope
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Data Analysis: Kinds of Data

Primary and Secondary Data

  • Primary - collected first hand from participants for the purpose of the investigation
  • Secondary - collected and analysed by someone other than the researcher

Evaluation

  • Primary
    • High validity
    • Targets relevent information
    • Time and effort
  • Secondary
    • Inexpensive and easy to access
    • Variation in the quality
    • Outdated and incomplete
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Data Analysis: Descriptive Statistics

Measures of Central Tendency

  • Mean - add them all up and divide by the number
  • Median - the middle value
  • Mode - most frequently occurring

Evaluation

  • Mean
    • Most sensitive and representative
    • Easily distrorted
  • Median
    • Not affected by extreme values
    • Less sensitive than the mean
  • Mode
    • Easy to calculate
    • Crude, unrepresentative
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Data Analysis: Descriptive Statistics

Measures of Dispersion

  • Range - subtract the lowest from the highest and add 1
  • Standard deviation - measures how much scores deviate from the mean

Evaluation

  • Range
    • Easy to calculate
    • May be unrepresentative of the data set
  • Standard deviation
    • Much more precise than the range
    • Can be distorted by extreme values
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Data Analysis: Graphs

Presentative and Display of Quantitative Data

  • Tables - raw scores are converted to descriptive statistics and summarised in a table
  • Bar charts - discrete categorical data represented for clear comparison; frequency of each category is the height of the bar
  • Scattergrams - shows the strength and direction of a relationship between co-variables

Distributions

  • Normal distributiion - bell curve; mean, median, and mode at the same point; tail never touches zero
  • Skewed distribution - negative skew leans right; positive skew leans left
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Mathematical Content

Mathematical Content

  • Percentages and fractions - convert one to the other, and to decimals
  • Decimals - appropriate number of significant figures
  • Ratios - part-to-whole; part-to-part
  • Mathematical symbols - =, >, <, >>, <<, 
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Introduction to Statistical Testing

Statistical Testing

  • Significance - results have not occurred by chance
  • Probability - 5% significance level; more stringent 1% level
  • Critical value - comparison with calculated value to determine significance

Sign Test

  • Criteria
    • Testing for difference
    • Nominal data
    • Repeated measures
  • Steps
    • Convert to nominal data
    • Add up pluses and minuses
    • S = less frequent sign
    • Compare calculated value of S with critical value
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Peer Review

Peer Review

  • Funding - approval of project proposals
  • Validation - quality check
  • Improvements - minor revisions or rejection of report

Evaluation

  • Anonymity
    • May permit unjustified criticisms by rivals
  • Publication bias
    • File drawer problem, creates false impression of current knowledge
  • Burying ground-breaking research
    • Maintains status'quo
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Psychology and the Economy

Examples

  • Attachment research
    • Equal care from mother and father
    • Means more effective contribution to economy
  • Mental health
    • Absenteeism due to moderate mental health (e.g. depression) issues costs the economy
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