Week 2

Question 1

Placebo effect

Answer 1

Person’s belief rather than actual experimental change alters their behavior

Question 2

Experimenter bias

Answer 2

• 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

Question 3

Observer bias

Answer 3

Observers’ expectations influence what they BELIEVE they observed and what they ACTUALLY observed

Question 4

Demand characteristics

Answer 4

People change their behavior when they know they’re being studied

Question 5

How to avoid demand characteristics (3 methods)

Answer 5

• 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

Question 6

Hawthorne Effect

Answer 6

Specific example of demand characteristics – Hawthorne noticed ppl worked harder in factory when they knew they were being watched

Question 7

Priming

Answer 7

Give someone a little exposure to something –> it subconsciously affects their behavior

Question 8

Double-blind study

Answer 8

• Method of avoiding bias
• neither researcher nor participant knows placement in IV
• Script

Question 9

Converging operations

Answer 9

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)

Question 10

Replication

Answer 10

Repeating a study to find similar outcome

Question 11

Types of brain scans

Answer 11

MRI - brain and structure
fMRI - active areas – measures blood flow in brain
EEG - electrical activity of brain

Question 12

Spatial resolution vs temporal resolution

Answer 12

spatial resolution – ability to determine location

temporal resolution – ability to determine timing

Question 13

Negatively vs positively skewed vs unskewed results

Answer 13

Neg: right-leaning

Pos: left-leaning

Unskewed: left half mirror image of right half

Question 14

Gaussian distribution

Answer 14

• Bell curve
• Freq highest in middle and decreases at extremities

Question 15

Two kinds of descriptive statistics

Answer 15

Central tendency: “typical” value of a dataset

Variability: the “spread” of values across dataset

Question 16

Central tendency

Answer 16

• “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

Question 17

Variability

Answer 17

• The distribution of values of a dataset
• Range: largest measurement minus smallest measurement
• Standard deviation: how each of the measurements differ from the mean

Question 18

Third-variable problem

Answer 18

Observed correlation might be caused by an unknown third variable

Question 19

Self-selection

Answer 19

A problem where something abt the participant determines which level if IV they’re in

Question 20

what does “p < .05” mean

Answer 20

Way for scientists to indicate statistically significant results – means there’s less than a 5% chance the results occurred by pure dumb luck

Question 21

Internal vs external validity

Answer 21

Internal: how valid the results of the study itself are

External: how applicable the results are to the real world

Question 22

Representativeness restriction

Answer 22

• “As we defined that variable…”
• Accounts for the fact that the results of a study depend on how the variable was defined

Question 23

Generalizability restriction

Answer 23

• “In the people we studied…”
• Accounts for fact that studied sample may not be representative of population

Question 24

Reliability restriction

Answer 24

• “It is likely that…”
• Accounts for the fact that results may be incorrect

Question 25

Type I vs Type II errors

Answer 25

Type I - False POSITIVE (fluke)

Type II - False NEGATIVE (flunk)

Question 26

Do researchers have to share the true nature of their study with their participant?

Answer 26

They don’t have to unless they were deceived