Title: Association between categorical (nominal or ordinal) and ratio/interval variables
Course: UGQuants (SSPS) > Section: Associations Between 2 Variables

Association between categorical (nominal or ordinal) and ratio/interval variables

The principle behind analysing a potential association between these combinations of variables remains exactly the same as was stated on association between only categorical variables: to compare how the distribution of values for one variable varies across different categories of another variable and thus to consider whether and to what degree one variable might be influencing the other. Similarly, it is again helpful to consider which variable is most likely to be the independent and which the dependent variable.

But the way we present the data for such associations is different from the contingency tables discussed in 2. Instead, we utilise the capacity of ratio/interval variables to be effectively summarised by a single number such as a measure of central tendency or spread. Of course, we can also summarise ordinal and nominal variables using the median and mode respectively as measures of central tendency, but in practice we seldom choose only to do this because doing so does not tell us anything about the distribution of cases that do not fall into the median or modal categories, and it is usually quite straightforward to present the distribution of all cases for a categorical variable in a table. But we know that this is often not true of interval and ratio variables, which tend to have large numbers of possible values.