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26 Cards in this Set
- Front
- Back
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David Hume
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- "Principle of Association"
- human habit of causal inference |
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Oskar Pfungst
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- Hero of "Clever Hans" horse story
- Showed correlation does NOT imply causation |
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Goals of Scientific Method
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- describe (phenomenon)
- explain (what's happening, mechanism) - predict (go beyond given) - control (intervene, better outcomes) |
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Data Collection Methods
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- self-report
- observation |
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Research Settings
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- lab
- field |
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Descriptive Research Design
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- case study
- survey - naturalistic observation |
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Correlational Research Design
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- positive relationship
- negative relationship - no relationship - correlation does NOT imply causation |
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Operationalization
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manipulate the IV
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Independent Variable
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(IV) what is changed in experimental research, what you manipulate in the experiment
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Dependent Variable
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(DV) what depends on the IV, the outcome from the experiment, what you observe
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Control of Extraneous Factors, Randomization
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necessary for experimental research
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Sample Representativeness
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adequate #? appropriate? assesses theoretical framework? adequate procedures?
*critiquing a study* |
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reliability
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consistent?
*critiquing a study* |
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validity
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tests what it is supposed to measure?
*critiquing a study* |
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central tendency
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??
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mode
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most common
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median
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middle point
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mean
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arithmetic mean, average
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range
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highest-lowest #s
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variability
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(stdev) average distance from mean
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normal curve
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when the mean - mode
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null hypothesis
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- H0
- means are from the same curve - differences are due to chance |
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alternative hypothesis
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- H1
- means are from different curves - differences are significant |
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p value
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- probability that H0 is true, data comes from the same population
- when p< .05, reject H0, accept H1 |
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Inferential Statistics
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necessary because nothing is ever 100% testable, one must always go beyond the given data
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When Critiquing a Study:
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- don't announce hypothesis to subjects
- large sample # - exactly same environment - examine the data / conclusions - consider meaningfulness of study - evaluate ethics of study |
