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26 Cards in this Set

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