lecture 2 - scientific method Flashcards

1
Q

external validity

A

can outcome of observation be applied and expected in other settings
- does it apply to other settings, people and time?

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2
Q

internal validity

A

does the study answer design and analysis answer the og research question

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3
Q

case studies

A
  • focuses on a specific case, mostly just 1 person
  • pro; give rich info
  • con: low external validity (doesnt always apply to everyone else)
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4
Q

naturalistic observation

A
  • examines what people do in natural context, in their own environemtns
    -con: reactivity: when people know they are being watched, they act differently
  • con: possible low internal validity
  • pro: can have high external validity (if no reactivity)
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5
Q

archival study

A
  • doing research using existing data
  • pro: less invasive
  • con: lack of quality control (dont exactly know if this information i true or good)
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6
Q

surveys

A
  • pro: ease of administration, convenient
  • con: response/error bias
  • malingering and social desirability - faking answers to make people feel bad for you
  • anonymity helps
  • con: ambiguity (do people fully understand what your trying to measure)
  • will answer differently based on how they interpret the questions
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7
Q

reliability

A
  • to be reliable a test must produce similar answers over an over again
  • internal validity
  • test-retest reliability
  • inter-rater reliability
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8
Q

internal consistency

A
  • do results agree
  • all answers should lead to similar and consistent results
  • shouldn’t have conflicting results
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9
Q

test-retest reliability

A
  • same test different timeline
  • will the same test provide the same results two days apart?
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10
Q

inter-rater reliability

A

do two people agree on the resuts

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11
Q

validity

A

valid if it measures what its supposed to measure
- face validity
- convergent validity
- divergent validity

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12
Q

face validity

A
  • does the test measures what its supposed to
  • does a survey ask about cars if they want to know how often someone bikes
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13
Q

convergent validity

A

test that measure the same things should have the same results

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14
Q

divergent validity

A

test that measure different things should have different results

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15
Q

correlation studies

A
  • related things but not causation
    two variables have a relationship
    advantage: can make predictions
    disadvantage: cannot infer causality
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16
Q

correlation graphs

A
  • positive if going up (both variables increasing)(+1)
  • negative if going down (one inc, one dec)(-1)
  • no correlation: straight line
  • closer dots are on scatter plots, more correlated
17
Q

illusory correlation

A

looks like theres a correlation but in reality there isnt
- jinx, or spiritual beliefs

18
Q

random assignment

A

randomly assigns people to groups in experimental design

19
Q

confounds

A

variable that can alternatively affect your variables
- can think that y cause x but really z is affecting them both
- could be placebo effect or
- participant demands (behaving the way researcher wants you to)
- or experimental effect (researcher has bias)

20
Q

experimental design

A
  • has random assignment
  • for cause and effect
  • has manipulation
21
Q

quasi-experimental design

A

no random assignment but still manipulation
- some things cant be random (marital status, ethnicity, experiences)

22
Q

W.E.I.R.D

A

mostly study weird samaples because we are in the western world
W: western
E: educated
I: industrialized
R: rich
D: democratic

23
Q

descriptive statistics

A
  • characterizes or summarizes the data
  • mean, median, mode
  • density function: formula that estimates the line of best fit
24
Q

positive skewed distribution (stats)

A
  • long tail on the right
  • mean gets pulled to the right
25
Q

negatively skewed distribution

A
  • long left tail
  • mean gets pulled to the left
  • median is in-between mean and mode
26
Q

normal distribution

A
  • symmetric distribution
  • mean median and mode are all in the middle at the peak
27
Q

inferential statistics

A
  • test that let us know if outcomes generalize to the greater population
  • if there is a difference, is it statistically significant
  • can we say that it applies to the population
  • use p test
28
Q

null hypothesis

A

hypothesis that says there is no effect
- trying to disprove it