In so-called bivariate data, two variables are examined together to determine whether there is coherence between the variables.
For two numeric variables, for example length and weight, a scatter plot is suitable.
For two category variables, for example gender and class, a crosstab is appropriate.
For a numeric and a category variable together, no suitable table or diagram is immediately available.
The solution is then to classify the numeric variable into categories. For example, you can organize a variable age into categories, such as young and adult. Of course, information is lost, but that is also the case with a simple bar chart.
| 4.5a | The Titanic dataset also includes the variable age. |
| You create a crosstab with three categories for that variable. |
You can investigate your impression of the relationship between gender and age further in cross table analysis.
The age categories are indicated by the labels: young, adult and old.
| 4.5b | Further research with diagrams. |
