CHAPTER 2 Flashcards

(39 cards)

1
Q

goal of research

A

continuously improve on tentative answers to questions

  • think and seek new knowledge
  • question what we know, explore unknown
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

research

A

exploration of the unknown thru data gathering

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

personality data

A

applies to psych triad using personality clues that we search for

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

funder’s second law

A

there aren’t any perfect indicators of personality, only ambiguous clues

must put tgt clues
- realize clues may be misleading bcs ambig

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

funder’s third law

A

smth beats nothing, 2/3 times

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

ways personality data can be collected

A
  • s data
  • i data
  • l data
  • b data
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

S data

A

self reports, usually surveys
- has high face validity

pros:
1. large amounts info: bcs know self best
2. access to psych triad
3. definitional truth: correct bcs you say it is i.e. i’m smart
4. causal force: self-efficacy—you become what you say you are

self-verification: try to make others see how you see yourself

cons:
1. bias: overly pos, desire privacy
2. error: active mem distortion, lack insight
3. too simple = careless

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

fish and water effect

A

an error w s data

ppl don’t notice constants in their personality i.e. always grumpy so don’t realize it

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

i data

A

informant report data: collected by informants i.e. coworkers, psychs, acquaintances

may be more accurate to ID -ve traits than S data

pros:
1. lots of info i.e. many informants
2. real-world basis: not controlled environ, more likely to be relevant
3. common sense: accounts for CONTEXT i.e. screamed at elevator vs thief
4. definitional truth: if others think it, it’s true
5. causal force: reputation affects expectations and opps

cons:
1. limited behav info
2. lack priv exp
3. error: likely to remember unusual behav
4. bias: prej and stereotype

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

judgments

A

based on observing ppl in context they know them from

collected via i data

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

letter of recommendation effect

A

bias in i data bcs ppl only offer informants w pos views of them

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

expectancy effect

A

causal force in i data

become the person others expect
- aka behavioural confirmation

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

L data

A

life outcomes data: verifiable, concrete, real-life evidence
- facts that may hold sig i.e. school records, med files, soc med

pros:
1. verifiable events
2. intrinsic importance
3. psych relevance

cons:
1. multideterminism: many reasons for evidence i..e recession causes unemployment, messy bcs of guests

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

B data

A

behavioural data: obs of daily life or in lab
- visible indication of personality
- can also be seen thru some personality tests

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

natural B data

A

natural B data: from daily life…diary and exp sampling methods

  • ear: electronically activated recorder
  • wearable cameras
  • soc med

ambulatory assessment: uses comp methods to access psych triad in daily activiites

pros: realistic
cons: difficult, desire contexts rarely happen

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

laboratory B data

A

experiments that make situation and record behav
- examine rxns, may measure phys behav
- represents diff to observe contexts

pros:
1. inc range of contexts
2. appearance of objectivity: still subjective judgments made

cons: diff and expensive, uncertain interpretation

17
Q

mixed data types

A

wide range of types of data relevant to personality

each w dis/advantages

18
Q

reliability

A

tendency of measurement instrument to provide the SAME INFO mult times

19
Q

measurement error

A

cumulative effect of extraneous influences on a test score

20
Q

states vs traits

A

traits more stable across situations w little variation

21
Q

factors undermining reliability

A
  1. low precision of measurement
  2. state of participant
  3. state of experimenters

some participants respond w/o thought, etc.

22
Q

ways to enhance reliability

A
  1. carefully
  2. use constant, structured procedures
  3. measure smth imp that engages participants
23
Q

aggregation

A

allow random influences to cancel each other out

  • esp imp for predicting behav
24
Q

spearman brown formula

A

formula in psychometrics

predicts deg to which a test’s reliability can be inc by adding more items

25
construct validation
gather as many constructs as possible...compare one measure to many
26
generalizability
deg to which test can be found in diverse circumstances ethical and cultural diversity shows vs no shows (ppl who don't arrive may be for a reason)
27
case method
can explain events, gen lessons, scientific principles - detailed descs, collect history and biographical info pros: 1. source for ideas i.e. theories 2. desc whole phenomenon 3. sometimes necessary to understand individ cons: unknown generalizability
28
experimental method
establishes CAUSAL RELATIONSHIP b/w indep vari and dep vari requires random assignment to experi and control groups test differs b/w groups to determine if difference is significant
29
between subject variable
ONE lvl of IV is gen to some participants, not to others i.e. bobo doll...cartoon model, filmed model, adult model
30
subject variables
pertains to the indiviudal subjects are classified and compared based on personality variables that are NOT manipulated i.e. perfectionists vs non-perfectionists
31
correlational method
establishes a relationship b/w 2 varis but DOES NOT say if causal - just measures amount of variable
32
why is correlational method bad
problems of causality: only says if correlation exists, not why directionality problem: can't tell which is cause, which is effect
33
how to fix correlational method
longitudinal method
34
third variable problem
unforeseen factor actually CAUSES the correlation
35
experimental vs correlational methods
both try to assess relationship b/w varis experimental MANIPULATES correlational MEASURES only experiments can determine causality
36
complications with experiments
- not always possible - artificial - often deceptive
37
mediator effect
link b/w varis exists mainly bcs of MUTUAL LINK with an intervening vari mediated is caused by IV and causes DV i.e. verbal abuse in childhood assoc w -ve self esteem, which is assoc w depression third variable is a mediator
38
demand characteristics
cues in an experiment that allow participant to figure out hypothesis and try to act accordingly please experimenter
39
cut-off scores
sometimes used to assign participants to groups - must use pre-established scores to determine traits i.e. introversion median is not good idea...cannot assume ppl in middle will have linear trend in personality