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23 Cards in this Set
- Front
- Back
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independent variable
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what is being manipulated in the experiment
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dependent variable
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what is measured, the result of the manipulations of the independent variable
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history
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threat to internal validity, events that occur outside the laboratory that influences results
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maturation
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threat to internal validity, people change over time
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testing
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threat to internal validity, people generally improve on the second test
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selection
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threat to internal validity, things about a person that you can't necessarily control (general characteristics or life history)
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instrumentation
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threat to internal validity, wrong instruments, wrong scale, precision error
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regression
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threat to internal validity, to the mean, people typically start at the extreme and move towards the mean on subsequent tests
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mortality
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threat to internal validity, participants drop from the study
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coding behavior
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coders must agree on evaluations and must remain consistent over time
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random selection
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suggests that you have access to the whole population, but this can never really occur since participants are limited
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between subjects
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participants are directly compared to participants in other conditions
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within subjects
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participants are manipulated, tested before and after a manipulation, and results are compared with self
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individual differences
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interferes with the collection of data, contributes to variability
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Assumptions of ANOVA (3 items)
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scores are normally distributed
homogeneity of variance observations are independent of one another |
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type I error
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rejecting the null hypothesis when the treatment actually has no effect (alpha)
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type II error
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Failing to reject the null hypothesis when the treatment actually has an effect (beta)
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factorial design
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every level of every factor is paired with every level of every factor
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Threats to Internal Validity (7 items)
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He Makes Traffic Stop in Real Madrid
History, Maturation, Testing, Selection, Instrumentation, Regression (to the mean), Mortality |
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Test for Simple Effects
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test for the effect of 1 independent variable at each other level of the independent variable (the effect of the factor on each level)
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SS btn
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global treatment of variability (the variability among cells and deviations from the total mean)
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df error (one-way ANOVA)
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N - K, where K is the number of levels (!)
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df error (two-way ANOVA)
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(n-1)(ab), where a and b are the number of levels in each independent variable (A and B)
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