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chapter 2 Flashcards

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1
Q

personality data

A

the scientist must find clues about personality, because that is the only real way to interpret it these are BLIS (behaviour, life, informant, and self report) clues.

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2
Q

kinds of data: life outcomes

A

obtained from archival records or self-report, or medical files ( or really anything that the subject has affected)
-from social media
-(these are the results of personality)
-

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3
Q

kinds of data: self (self judgments or self reports)

A

usually questionaires or surveys about yourself

  • this is the most common type of data gathering
  • high face validity (looks like it is going to measure what it is supposed to measure)
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4
Q

kinds of data: informant

A

this comes from aquantances, coworkers, and others that are close to the subject

  • there is no training or expertise required
  • it is based on whatever context the informant knows them from
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5
Q

kinds of data: behavioural

A

the most visible indication of an individual’s personality, it is watching the behaviour of a person

there are 2 ways to see this: natural, and labratory

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6
Q

kinds of data: behavioural: natural data

A

based on real life

  • can come from a diary or an electronically activated recorder, anything that helps to observe people in a natural setting
  • this is however really difficult to get this information
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7
Q

kinds of data: behavioural: labratory data

A

this is using experiments

  • so they make a situation happen and record the behaviour
  • this is good for real life situations that are hard to observe directly
  • this data also includes physiological measures (measuring blood pressure, and other body responses)
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8
Q

3 issues in quality of data

A

reliability, validity, generalizability

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9
Q

reliability (define)

A

this is how reliable the test it, if it gets the same sort of results each time there is a test, if it went wrong there would be a measurement error

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10
Q

validity

A

-this is something that sees that your test is measuring what it is supposed to measure
construct validation: the process of testing the assumption behind a construct

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11
Q

generalizability

A

do the results apply to more people than just the ones assessed

  • shows vs no shows (these are different types of people)
  • gender bias
  • ethnic and cultural diversity
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12
Q

case method (ideographic research) (pros and cons)

A

the goal is to understand one person

  • can explain specific events and scientific principles
    advantages: can be a source of ideas about other people too, it does complete justice to the topic, sometimes necessary for understanding an individual
    dissadvantages: no control, and unknown generalizability
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13
Q

correlational vs experimental methods

A
  • they both attempt to assess the relationship between two variables
  • the experimental method manipulates the variable
  • and the correlational method measures it without manipulation (so measures both variables and see how they relate that way)
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14
Q

correlational research and the problems with it

A

this is when you measure two different variables and you see hwo they are related using the measurements that you took

the problems with this is that the correlation does not necessarily mean causation,
-there could be a third variable that is causeing both of the variables

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15
Q

what is experimental research

A

this is a research design where the casual relationship between x and y is determined by randomly assigning participants to experimental groups charactarized by differing levels of x and measuring y in the group

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16
Q

unique features of experimental research

A

1) manipulation
- researcher controls the indipendant variable (the cause)
- evaluates the effect it has on the dependant variable (the effect)
2) random assignment
- the person has an equal chance of participating in any condition
- distributes all other variables equally amoung the experimental groups

17
Q

kinds of data: self: pros

A
  • lots of info: can reflect complex aspects of character that you are the only one with access to
  • access to thoughts and feelings
  • simple and easy: it is often cheap and reletively easy to make
18
Q

kinds of data: self: cons

A
  • they may choose to not tell you: they minght want to keep it a secret
  • it is too simple: might need something more complex
  • maybe they cant tell you: they may not be aware of something themselves
19
Q

kinds of data: informant: pros

A
  • real-world basis: this is an observation of the subject in the real world, in real situations
  • large ammount of information: the aquantance has seen the subject in many different situations
  • some kinds of “I” data are true by definition
  • causal force: you see the persons rep, and to some degree people become what others expect them to be
20
Q

kind of data: informant: cons

A
  • limited behavioural info: you only see them in the context that they show you (they may be different with others)
  • there may be bias that the subject has conveyed to them: they may not like the subject, or really like them
  • there is lack of private experience: you dont know their inner mental life
  • error: because you are human you sometimes make the wrong judgment about the subject
21
Q

data: life outcomes: pros

A
  • objective and verifiable: this data is concrete and can sometimes be expressed in numerical form (it is very precise)
  • intrinsic importance: the psychologist finds exactly what they want to know
  • psychological relevance: very informative about psychological variables
22
Q

data: life outcomes: cons

A

lack of possible psychological relevance (multi-determination): so what you see may not be a result of their personality, or even them (a messy room could be from a guest)

23
Q

data: behavioural: pros

A
  • appearance of objectivity: direct gathering of info, doesn’t have to take someones word for it
  • wide range of contexts: for labratory B data they can just create the context that they need
24
Q

data: behavioural: cons

A
  • difficult and expensive: all the stuff is very labour intensive
  • uncertain interpretation: info can be misleading and you arent certain what certain things mean
25
Q

how to improve reliability

A
  • be careful: double check things
  • use a scripted procedure (keep it constant)
  • aggregation (allow random influences to cancel each other out, averaging things)
  • measure something important (so that the participants actually care)
26
Q

things that undermine reliability

A
  • low precision of measurement:
  • the state of the participant:
  • the state of the experimenter:
  • the environment:

psych of personality (6 decks)

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