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17 Cards in this Set
- Front
- Back
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causality requires
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-covariation
-directionality -control of other possible causes |
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correlation coefficient
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=r
demonstrates value of variablitiy |
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range
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-1.00 to +1.00
positive:as scores one 1 variable inc, scores on other variable inc negative:as scores on 1 variable inc, scores on other dec |
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magnitude
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strength of linear relationship
farther from zero, the stronger the relationship (-.70 has great magnitude than .40) |
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interpreting r
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<0.10 is trivial
0.10< r <0.30 is weak 0.30< r <0.50 is moderate r>0.5 is strong r^2 tells how much variance is accounted for |
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p-value
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tells whether correlation is statistically significant or not
Null hypothesis: no relationship, r=0 alternative hypothesis: positive, r>0.00 or negative, r<0.00 |
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probablity
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if prob. that correlation = 0.00 is low (less than 5%) than can say correlation is statistically significant and reject null hypothesis
however, cannot 'prove' alternative hypothesis |
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outliers
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+/- 3 sd from the mean
can have big impact on r |
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on-line vs. off-line
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on-line can boost size of correlation
off-line can drag correlation down |
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regression
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prediciting scores on 1 variable based on the participant's scores on another variable
assess relationships of >1 predictors simultaneously |
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multiple regression
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assessing the relationship b/w mulitple predictor variables and an outcome variable
predicting an outcome variable based on predictor scores linear relationship, best fitting line |
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moderator variables
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interactions:when the relationships b/w a predictor and outcome variable depends on the value of another variable (moderator)
ex. licorice color; more ppl like red than black |
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moderator variables can help understand...
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can be a 3rd variable that influences the relationship b/w a predictor and outcome variable
understand the relationship establish boundary conditions |
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types of moderator variables
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Discrete: examine predictor-outcome variable for each category (licorice either black or red)
Continuous: one solution- change continuous to discrete high category- group > +1 sd low category- group < -1 sd |
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moderator analysis
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predictor, moderator, and new interaction variable (PxM) are entered into regression equation
high values: both P and M are large low values: either P, M, or both values are small |
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mediator variables
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an intervening 3rd variable that (partly) explains the influence of the predictor on the outcome
predictor incluences mediator, which influences outcome variable ex. viewing violent tv-->arousal (mediated effect)-->agressive play |
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mediated effect if..
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the magnitude of direct relationship b/w the predictor and outcome is drastically reduced (or 0) when the relationship b/w the mediator and outcome is considered
the predictor and mediator are related |
