Chapter 8: Bivariate Correlational Research Flashcards
Bivariate Correlation
An association that involves 2 variables
aka. Bivariate Association
Categorical Variable
falls to one category or another
Mean
the average; a measure of central tendency
What do effect sizes indicate?
the importance of a result
“when all else is equal a larger effect size is more important than a small one”
Confidence internals in larger estimates
larger estimates provide smaller and more precise confidence intervals
Statistically significant interval
p < 0.05, unlikely that the result emerged by chance or by the null hypothesis
Confidence interval containing zero
can’t rule out that the association is zero, common to say “the association is not statistically significant”
Outlier
Score that’s much higher or lower than rest of sample, causes disproportionate influence when scores are extreme on both variables
Restriction of Range
In a bivariate correlation, the absence of a full range of possible scores on one of the variables, so the relationship from the sample underestimates the true correlation
Curvilinear Association
an association between two variables that isn’t a strait line (U or inverted U shape)
Covariance of Cause and Effect
the results must show a correlation or association between the cause and the effect variable(establishing causation)
Temporal Precedence
- the method must insure that the cause variable preceded the effect variable (establishing causation)
Internal Validity
No other explanations between the two variables (establishing causation)
Directionality Problem
in a correlational study, both variable are measured around the same time thus making it unclear which variable in association came first (think temporal precedence)
Third Variable Problem
in a correlational study, the existence of a plausible alternative explanation for the association between two variables (think internal validity)