Placebo effect
Person’s belief rather than actual experimental change alters their behavior
Experimenter bias
- Experimenter’s expectations influence outcome of study
- they “see” what they want to “see”
- Not necessarily malicious or intentional
- Might behave or treat participants differently
- Rosenthal & Fode: smart rats vs dull rats – “smart” rats did better than “dull” rats despite being the same
Observer bias
Observers’ expectations influence what they BELIEVE they observed and what they ACTUALLY observed
Demand characteristics
People change their behavior when they know they’re being studied
How to avoid demand characteristics (3 methods)
- Naturalistic observation: observe ppl in natural conditions
- Privacy and control: ppl less likely to be influenced by demand characteristics if they won’t be held responsible for their own actions
- Unawareness: ppl being observed unaware of true nature of observation
Hawthorne Effect
Specific example of demand characteristics – Hawthorne noticed ppl worked harder in factory when they knew they were being watched
Priming
Give someone a little exposure to something –> it subconsciously affects their behavior
Double-blind study
- Method of avoiding bias
- neither researcher nor participant knows placement in IV
- Script
Converging operations
Method where multiple operational defs of a variable are used in or across different studies (e.g. examining data when wealth is measured with net worth, yearly income, etc and seeing how relationship holds)
Replication
Repeating a study to find similar outcome
Types of brain scans
MRI - brain and structure
fMRI - active areas – measures blood flow in brain
EEG - electrical activity of brain
Spatial resolution vs temporal resolution
spatial resolution – ability to determine location
temporal resolution – ability to determine timing
Negatively vs positively skewed vs unskewed results
Neg: right-leaning
Pos: left-leaning
Unskewed: left half mirror image of right half
Gaussian distribution
- Bell curve
- Freq highest in middle and decreases at extremities
Two kinds of descriptive statistics
Central tendency: “typical” value of a dataset
Variability: the “spread” of values across dataset
Central tendency
- “Typical” value of a dataset
- Mean, median, mode
- When a distribution is skewed, MMM will have different values, so you should never calculate only one of them
Variability
- The distribution of values of a dataset
- Range: largest measurement minus smallest measurement
- Standard deviation: how each of the measurements differ from the mean
Third-variable problem
Observed correlation might be caused by an unknown third variable
Self-selection
A problem where something abt the participant determines which level if IV they’re in
what does “p < .05” mean
Way for scientists to indicate statistically significant results – means there’s less than a 5% chance the results occurred by pure dumb luck
Internal vs external validity
Internal: how valid the results of the study itself are
External: how applicable the results are to the real world
Representativeness restriction
- “As we defined that variable…”
- Accounts for the fact that the results of a study depend on how the variable was defined
Generalizability restriction
- “In the people we studied…”
- Accounts for fact that studied sample may not be representative of population
Reliability restriction
- “It is likely that…”
- Accounts for the fact that results may be incorrect
