Research Methods
All notes needed for Research Methods, A2 Unit 4 Psychology (AQA A)
- Created by: charlotte
- Created on: 13-05-12 14:33
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
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
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
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
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
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)
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
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)
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%)
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
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
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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