extra credit stats types Flashcards
- Examining the relationship between to variables
Bivariate anlysis
Usually used when you have two nominal variables you want to compare
* Can simply use cross-tabulation tables
* Can also use Chi-square (2) to test for statistical significance
Contingency tables
Used to test whether group means are statistically significantly different from each
other
* Independent samples t-tests versus paired(aka dependent) samples t-tests
T-tests
Again, used for assessing the relationship between two variables (review previous
slide on correlation types)
* If we square the correlational value, we have the proportion of explained variance
Correlations
Principally used to determine whether three or more groups significantly vary in
relation to each other
* We can determine if the mean values of a measure for each group are significantly different from each other
* Example: we have three groups of officers and want to know whether the number of arrests significantly differ between groups
ANOVAs
Based on the principle that over time things tend to regress toward the mean
* Use one variable (IV) to predict another variable (DV)
* Several assumptions must be met in order to use linear regression (Normality,
linearity, homoscedasticity)
Bivariate regression
Same as above, but you are assessing the predictive potential of multiple IVs and control variables in relation to a dependent variable
multivariate regression