L4 - Methods of Psychology Flashcards
1
Q
Research Methods:
A
The lesson of Clever Hans (horse that could do “math”): To test specific hypotheses you need to constrain extraneous variables and focus on what you are manipulating (IV) = ↑ Control and analysis (at the cost of a more artificial experiment)
Ordered from Least → Most control:
- Introspection
- Naturalistic Observation
- Case History
- Survey
- Test
- Correlation
- Experiment
2
Q
Introspection:
A
- “Looking inward”; Systematic/structured way of observing our own consciousness + a verbal report of our observations
- Non-scientific, subjective (no separation between observer and observed), “mentalist” psychology
- Underlies contemporary self-report methods
3
Q
Naturalistic observation:
A
- Objectively studying events naturally, without intervention
- Good starting point but often difficult to remain objective without intervention (e.g. observe social interaction whilst not participating in it)
4
Q
Case history/study:
A
- Biography for a single individually obtained retrospectively; often via interviews
- Essential in clinical psych etc. (using case studies as a form of “storytelling” is persuasive) but observations cannot be generalised
- Paradigms: Biological, psychodynamic, humanistic
5
Q
Surveys:
A
- Quantitative measure of responses to questions; often via an interview or questionnaire of a large sample
- Easy to perform but easily distorted (e.g. “What grade do you think you deserve?” Everyone would put a 7)
6
Q
Tests:
A
- Quantitative measure of performance relative to a preset norm
- E.g. Mid-semester exam
7
Q
Correlation:
A
- Statistical calculation of direction and degree of relationship between any 2+ variables (“what goes with what”)
-
Correlation coefficient (f) = Degree (strength) and direction of covariance (relationship) between 2+ variables
- Strength: How far value is from 0 with a range of -1 → +1 (correlation of -1 is same strength as + 1); closer to 0 = weaker correlation
- Direction: Positive = Direct relationship; Negative = Inverse relationship; 0 = No relationship
- Correlation fallacy: Even when strong, correlations CANNOT infer causality; there may be an additional variable (e.g. foot size of children is strongly correlated with intelligence but this is only because children with larger feet are usually older)
8
Q
Experiment:
A
- Method of manipulating one set of variables (IV) while observing & measuring the effect on another set (DV), with other factors being held equivalent (random & control variables)
- If a change of IV = Significant change in DV, we can infer that the IV has a causal relationship with the DV
- Paradigms: Behavioral, cognitive (e.g. The Stroop Effect), biological
- “Research lives in correlation and experimental”
9
Q
Common Sources of Bias (Distortion) in Research:
A
- Sampling Bias
- Subject Bias
- Experimenter Bias
- Operational Definitions
10
Q
Sampling Bias:
A
- Is the sample studied representative of the population of interest?
- Affects generalisability of conclusions
- Solution: careful design – don’t just test anyone/everyone
11
Q
Subject Bias:
A
- ‘Hawthorne’ or placebo effects
- Early (1920s) research in the applied area of Industrial Psychology
- What environmental factors affect worker productivity? (Hawthorne was the name of the production company)
- The main experiment related to workplace lighting
- Were the subjects responding to their expectations, rather than to the experimental manipulations?
- Remember, the experimenters were with the subjects when changes were made
- Solution: single ‘blind’ research – subjects are less aware of what’s going on
12
Q
Experimenter Bias:
A
- Rosenthal’ effects (Robert Rosenthal)
- 1960s
- Initial studies were on classroom students
- Student ‘experimenters’ observed the learning behaviour of rats in two conditions: “dull” versus “smart” rats
- Are the researchers influencing the behaviours they are observing?
- Favours one group over the other
- Solution: double ‘blind’ research – experimenter and subjects less aware of what’s going on
13
Q
Operational Definitions:
A
- Defining variables in terms of the operations (methods) used to observe/measure/manipulate them
- Needs to be very clear what you are measuring