Quantitative Research Flashcards
Week 1
Identify the contributions of Descartes and Locke to understanding the mind and behaviour
Descartes
- Rationalism - use of reason and logic to derive the truth; senses can deceive
- Cartesian dualism - mind-body dualism - mind and body are conceptually separate
Locke
- Disagreed with Descartes
- Empiricism - knowledge is constructed by experiences and sensation
- Theory that environment shapes the mind was later adopted by Behaviourism movement
Week 1
Recognise the work of Fechner and Wundt on the development of experimental psychology
Fechner
- Developed psychophysics
– Relations between sensations and the physical stimuli producing them
- First experimental psychologist
- United the mind and body mathematically
- Led to developments of psychometrics and experimental psychology
Wundt
- Established the first psychology laboratory at the University of Leipzig in 1879
- “Physiological psychology”
- Structuralism - breaking down mental processes into their basic elements
- Use of introspection: training people to objectively analyse the content of their own thoughts
- Developed the first journal of Experimental Psychology. ‘Philosophical Studies’ (1883)
Week 1
Describe the contributions of Darwin and Galton to methods and analysis used in psychology
Darwin
- Places ‘human nature’ in the wider context of evolutionary change
- Functionalism - how human behaviour and mental processes serve to adapt an individual to an ever-changing environment
- Led to the systematic study of individual differences: intelligence and personality tests
- First scientific attempt to study emotions
Galton
- Intelligence is inherent - nature plays no role
- Argued for eugenics
- Measured human ability and classified it - individual differences in human abilities
- Questionnaire design
- Normal distribution
- Intelligence tests (& eugenics)
- Correlation
- Twin study methodology
Week 1
Give examples of inductive and deductive reasoning
Inductive
- Reasoning from singular statement (or premises) to the probable validity of a conclusion
- Observation -> Pattern -> Hypothesis -> Theory
- Dog has always barked at postman -> postman arrives -> dog will probably bark
Deductive
- Reasoning from general statements (or premises) to a logical and certain conclusion
- Theory -> Hypothesis -> Observation -> Confirmation
- Only dogs bark -> subject barks -> subject is a dog
Week 2
Appreciate why we conduct research in psychology, and the role of evidence in challenging common-sense beliefs and intuition
Why We Conduct Research
- Process of generating and testing new ideas
- The world is changing - research is needed to further our knowledge
- Avoid myths from intuition
- Studies and theories are underpinned by research
Role of Evidence
- To inform knowledge
- Challenge myths - e.g., Does mobile phone use negatively impact on children’s grammar? (Wood, Kemp & Waldron, 2014)
- Psychology would not exist without research
Week 2
Appreciate the importance of using hypotheses in quantitative psychology
- Popper (1963) - theories should be phrased in a way that makes it possible to show how they could be wrong
- Must be testable, precise and falsifiable
Week 2
Be aware of the stages in the hypothetico-deductive method
- Identify a problem
- Define a problem
- Generate hypothesis/es to test the problem
- Design the research to test hypothesis/es
- Collect the data
- Analyse the data
- Interpretation of the results
Week 2
Explain why generalisability and replicability are fundamental to quantitative research in psychology
Generalisability
- Only a small (but representative) sample is needed to generalise to a wider population
- Statistics can be used to generalise
Replicability
- To ensure that the generalisations we make from our research samples hold true for the population
- Theories are not based on only one study
- Avoid ‘flukes’
- Increase confidence in our results
- Can involve minor modifications
Week 2
Recognise the methods of data collection used in quantitative psychology, namely experiments (including quasi experiments and clinical trials/RCTs), correlational studies, and questionnaires
Experiments
- Randomised Controlled Trials (RTCs)
– Most rigorous form of research
– Used to measure the effect of an intervention by ranomly assigning individuals to intervention or control group
–Participants and researcher are blinded to the condition
- True Experiments
– Laboratory-based and fully controlled
– Experimental manipulation
– Standardised procedure
– Random allocations of participants to conditions
- Quasi Experiments
– Like a true experiment, but lacks either/both:
– Random assignment
– Full control over the independent variable
Correlational Studies
- Used to determine a relationship between factors
- Non-manipulated variables
- Useful when you are unable to perform an experiment
- Observe natural variation in variables and measure the correlation between both
Questionnaires
- Commonly used to collect data in correlational studies
- Used to objectively measure a particular concept
- Psychometrics: area of study concerned with the theory and technique of psychological measurement
– Diagnosis or screening for clinical purposes
– E.g., Beck Depression Inventory, Eating Disorders Examination Questionnaire
Week 3
Be able to identify the independent and dependent variables of a study
Independent
- Variable that the experimenter manipulates as a bases for making predictions about DV
Dependent
- Variable that is measured or recorded in an experiment (outcome)
Week 3
Appreciate the different types of variables used in psychology (continuous, discrete, categorical) and be able to identify variables in each category
Continuous
- Can take value within any given range, doesn’t change in discrete jumps
- Temperature, anxiety levels
Discrete
- Can only take on certain discrete values within the range
- Number of cars owned, number of children in a family
Categorical
- Value that the variable takes is in a category
- Gender, occupation, ethnicity
Week 3
Recognise the differences between within- and between-subjects designs and when it is suitable to use each, and appreciate the use of counterbalancing
Within-Subjects
- Repeated measures
- Same participants in every condition of the IV
- Less participants needed
Between-Subjects
- Independent groups
- Different participants in each condition of the IV
- Lots of participants needed
Counterbalancing
- One half of participants complete Condition A first; one half complete Condition B first
- Spreads order effects across both conditions of the IV
- Full or partial
Week 3
Appreciate what ‘sample’ and ‘population’ mean in psychology research, and the different types of sampling methods most commonly used in quantitative research
Sample
- The group selected from the population to participate in research
Methods
- Probability-based - everyone in the target population has an equal probability of being selected
– Simple random - Every member of the population of interest has an equal chance of being selected
– Systematic random - select every nth from the population
– Stratified random - random sample from various sub-sections of the population
- Non-probability - sample is not structured to approximate the population
– Opportunity/convenience
– Self-selected
– Online
Population
- A group that shares a common set of characteristics; the wider group to learn about
Week 4
Appreciate what is meant by the term ‘ethics’, and why it is important that ethical guidelines are adhered to in research and applied psychology
- Responsible and morally right conduct
- Psychologists have a duty of care to protect human and animal participants and clients from harm
Week 4
Be familiar with the BPS Code of Ethics and Conduct (2021) and the BPS Code of Human Research Ethics (2021)
BPS Code of Ethics and Conduct (2021)
- Respect - dignity, privacy and confidentiality, informed consent, no inappropriate use of power, compassion
- Competence - provide services to a professional standard
- Responsibility - professional accountability, use knowledge and skills appropriately
- Integrity - honest, unbiased and fair, avoid conflicts of interest and maintain personal and professional boundaries
BPS Code of Human Research Ethics (2021)
- Risk
- Valid consent & right to withdraw
- Confidentiality
- Deception
- Debriefing
Week 4
Be able to describe the following issues related to ethics: risk; consent; the right to withdraw; confidentiality; deception; and debriefing
Risk - Any potential physical/psychological harm, discomfort or stress to human participants that a research project may generate
Consent - Agreement to freely and voluntarily participate with the full knowledge of the content and participant rights
Valid - Over 18’s, Under 16’s with parental consent
Right to withdraw - Participants should be made aware of the voluntary nature of research and their right to withdraw at any time with no adverse consequences or penalty
Confidentiality - Information should be appropriately deidentified and not be able to be traced back to them
Deception - Deliberately providing incorrect information
Debriefing - Informing participants about the full nature or rationale of a study after participation and attempting to reverse any potential negative side effects
Week 4
Be able to describe ethical issues posed by contemporary areas including: internet research, clinical trials, and research using animals
Internet Mediated Research
- Valid consent - ensuring age of participants, ensuring that participants have fully engaged in consent procedures
- Confidentiality - IP addresses - issues with anonymity
- Debriefing - those who don’t participate for the full duration may not be debriefed
Clinical Trials
- Risks - do benefits outweigh risk?
- Is informed consent truly possible?
- Placebo and deception
Research with Animals
- Does the research threaten health and wellbeing?
- Is it fair to study animals to improve the human condition?
Week 4
Begin to develop a personal awareness of how to act ethically as a psychologist
Acting Ethically
- Collective responsibility - ask if unsure
Week 5
Be aware of the different levels of data measurement (nominal, ordinal, interval and ratio) and be able to identify examples of each type of data
Nominal
- Categorical
- Gender, ethnicity, job type
- Numbers are given to distinguish between categories, with no particular order to rank importance
- 0 male, 1 female, 2 non-binary, 3 other, 4 prefer to not say
Ordinal
- Categorical
- Using a scale to put people into an order/rank
- E.g., position in a race: 1st, 2nd, 3rd…
- Size of number does represent something
- However, size or difference between numbers, nor the ratio, is informative
Interval
- Quantifiable
- Puts scores in order, however differences between numbers are equal
- E.g., temperature, 0-10 = 10-20
- However, 10oc isn’t half as warm as 20oc
- There is no absolute 0 - 0oc doesn’t equate to 0, or no heat/temperature
Ratio
- Quantifiable
- Same as interval data, but there is an absolute zero
- E.g., height, test score, speed of a car
Week 5
Distinguish between different types of the central tendency, namely mean, median and mode, and recognise when it is appropriate to report each
Mean
- Sum of scores divided by number of scores in the sample
- Most commonly reported
- Most appropriate for ‘normal’ data
Median
- The middle score/value once all scores in the sample have been put in rank order
- Less commonly reported than the mean
- Non-normal data
Mode
- Most frequently occurring score/category of scores
- Least commonly reported, useful for categorical variables
- Bimodal = 2 modes; Multimodal = several modes
Week 5
Explain what population mean and sample mean are, and recognise the issue of sampling error
Population Mean
- Typical score in a population
- E.g., population mean for IQ = 104
Sample Mean
- The mean score of the sample taken from the population
Sampling Error
- The difference between the sample statistic and the population statistic
- Generally, the larger the sample, the closer the sample and population means will be
Week 5
Be familiar with bar charts and histograms and their uses
Bar Charts
- Used to summarise a categorical variable
- x axis represents the categorical variable
- y axis represents frequency, average, percentage, etc.
- Separate bars - unrelated categories
Histograms
- Type of bar chart for continuous variables
- Bars not separated & equal width
- Illustrate whole data set
- All values are represented, even if empty
- x axis: details of score on variable
- y axis: frequency of scores’ occurrence