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Glossary
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B
bivariate relationships - A relationship between two variables.
C
clustered bar graph - A graphical display of the relationship between two variables; shows the distribution of the dependent variable with a clustered set of bars for each category of the independent variable.
column percentages - The percentages that break down the distribution of the variable that is in the columns of a cross-tabulation; calculated by dividing the frequency in a cell by the total number of cases in the column.
cross-tabulation - A table that presents the frequency distribution for the dependent variable separately for each category of the independent variable.
D
dependent variable - A variable that is affected by another variable.
direction of relationship - Used with variables that are ordinal or interval-ratio. Indicates whether values of the dependent variable increase (with a positive direction) or decrease (with a negative direction) as values of the independent variable increase.
I
independent variable - A variable that causes a change in another variable.
N
negative relationship - A relationship between two ordinal or interval-ratio variables in which the values of the dependent variable decrease as values of the independent variable increase.
P
positive relationship - A relationship between two ordinal or interval-ratio variables in which the values of the dependent variable increase as values of the independent variable increase.
R
row percentages - Used in cross-tabulation; the percentage of the group in the row that falls into each category of the other variable. Calculated by dividing the frequency in a cell by the total number of cases in the row.
S
stacked bar graph - A graphical display that shows the distribution of the dependent variable with just one bar for each category of the independent variable.
strength of relationship - In a cross-tabulation, refers to the sizes of the differences in percentages across categories of the independent variable. In correlation, refers to how closely two variables are related to each other as reflected in the correlation coefficient.
