Research Methods

All notes needed for Research Methods, A2 Unit 4 Psychology (AQA A)

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Features of Science

Replicability; can be repeated and similar results are reproduced to test the reliability

Objectivity; studies are not affected by bias, opinions and emotions

Theory of Construction; looking at evidence and facts to make a theory

Induction; reasoning from the particular to the general,leading to a general law

The Hypothetico-deduction model; theories about behaviour, generating hypotheses that can be falsified

Deductive method best as involves proposing theory allowing researchers to seek falsification, by actively searching for ways to disprove the theory (KARL POPPER)

Falisified; method put under scrutiny and ability to be tested

Empiricism; information gained through direct observations or experiments

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Is Psychology a Science?

Common Sense; logical experiements based on own experiences are rarely tested and accepted as fact. Not scientific as not objective.

Belief-Based; beliefs, religious or spiritual have little or no evidence so is not scientific

Pseudoscience; "fake science" for example Cyrill

  • Psychology based on human behaviour, which can not be objective as humans are subjective in nature
  • Although this is a common problem in all scientific research for experimenter bias
  • Does not have a paradigm (shared set of assumptions) e.g. behavioural, cognitive & biological approaches (KUHN)
  • Uses Idiographic approach taking into account individual cases but science generalises using a nomothetic approach
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Validating New Knowledge

Journals of Psychology;

  • Media Psychology
  • Mathematical & statistical Psychology
  • British Journal of Psychology

Peer Review; the scrunity of research by independant peers, preventing incorrect data getting published

  • Consistency within previous knowledge; research should 'fit' paradigm, otherwise it becomes suspicious & can be rejected. Acts as conseravtive force to remain the status quo, not allowing for change.
  • Values in science;
  • Bias in peer review; is a appraisal process, as reviewers theoretical view may differ from manuscript. There is institution bias due to competition for university funding & alpha bias as male researchers are favoured
  • File draw phenomenon; publishers favour positive results & if the null is proven it is unlikely to be published so distorts understanding of topics
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Reporting Psychological Investigations

Abstract; summary of study

Intro & Aim; what research intends to study

Methodology; detailed description of research procedure (replication)

Results; what research found

Discussion; offer explanations & limitations

References; details of journals mentioned

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Reliability & Validity

Reliability; if repeated, the same or similar results will be found

Internal reliability; consistency of measure within study

External reliability; ability to replicate results

Validity; study measures what it is meant to measure

Internal validity; controlling all variables

External validity; extent findings can be generalised

Bias & Operationalising your variables is important in improving the validity

  • Test re-test, Inter-rater reliability, Pilot study & Split-half method
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Ethical Issues

2006 BPS Guidelines;

Respect - dignity & worth to all persons (privacy, confidentiality, informed consent & right to withdraw

Competence - maintain high standards in professional work

Responsibility - protecting from harm and debriefing participants

Integrity - be accurate and honest in work

Non-Human Animal Experiments;

  • Offer greater control & objectivity
  • Use animals where can't use humans
  • Have enough physiological & evolutionary past in common to justify conclusions
  • Extrapolation of findings to humans
  • Unethical due to sense of self (respond to pain and some conscious awareness)
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Graphical Representation of Data

Correlations coefficient; informs how closely co-variables are related, -1 & +1

Scattergraph's; correlations of 2 variables

Bar Charts; plotting discontinuous data

Histograms; plotting continuous data

Frequency Polygon; continuous variables

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Quantitative Data

Measures of Central Tendency -

Mean; in interval or ratio data

Medium; in ordinal data

Mode; in nominal data

Measures of Dispersion; range & standard deviation (how scores deviate from mean)

Levels of Measurement;

Nominal; frequency (categories)

Ordinal; ordered or ranked (uses scale)

Interval; units of equal intervals (scores, time)

Ratio; interval data but can go into negatives (temp)

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Probability & Significance

Probability; look at patterns within results, to establish if by chance.

Significance; where there is low probability that chance responsible (eliminating or accepting the null hypothesis)

Errors;

  • Type One Errors (False-Positive); wrongly accept alternative hypothesis & wrongly reject null hypothesis as results due to chance

Caused by high significance level (10%)

  • Type Two Errors (False-Negative); wrongly accept null hypothesis but results are accurate

Caused by low significance level (1%)

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Inferential Statistics

Chi-squared

  • difference in two conditions or association between co-variables
  • data nominal (not percentage) & independent groups

Spearman's Rho

  • correlation between co-variables
  • data ordinal & repeated measures

Mann-Whitney 

  • difference between two sets of data
  • data ordinal & independent groups

Wilcoxon

  • difference between two sets of data
  • data interval & repeated measures
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Qualitative Data - Thematic Analysis

Verbatim; writing word for word what the participant says in interviews

Thematic Analysis; identifying themes that occur to explore P's experience

Inductive; no preconception about themes

Theoretical; idea of themes from prior research

Process of Thematic Analysis

  • Coding; identify themes in each data set
  • Cluster of themes; group list of themes
  • Table of themes; identify and quote themes
  • Interpretations; identify similarities, difference and use knowledge to interpret what's been found

Data is user friendly to public, with rich detail and understanding of experience but problem of subjectivity as interpretation may differ and there is a lack of control in scientific method

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Content Analysis

Content Analysis; turning qualitative to quantitative data for statistical analysis

Process of Content Analysis

  • Coding; into words, themes ect.
  • Assessing frequency; frequency table of how many times occurs
  • Statistical test; appropriate stats test for data
  • Conclusions; describe what's been found

Data is more manageable, & easy to replicate, being objective and patterns can be identified using statistical methods but it is reductionist as richness of data is lost and categorisation may be biased

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