class: left, top, title-slide .title[ # Visualization 2
Numerical vs. Categorical Data ] .author[ ### Keith VanderLinden
Calvin University ] --- # Characteristics of Data Visualizations Data visualizations vary according to the: - Number of variables being plotted: - Univariate - Bivariate - Multivariate - Type of variables being plotted: - Numerical: - Continuous - Discrete - Categorical: - Ordinal - Non-ordinal ??? Variable Number - *Univariate* data analysis - distribution of single variable - *Bivariate* data analysis - relationship between two variables - *Multivariate* data analysis - relationship between many variables at once, usually focusing on bivariate relationships while conditioning for others Variable Type - Numerical variables can be classified as: - *Continuous*: infinite number of values - *Discrete*: only non-negative whole numbers - If the variable is categorical, we can determine if it is *ordinal* based on whether or not the levels have a natural ordering. --- # Canonical Plot Types Response Variable (y) | Explanatory Variable (x) | Plot Type | :-------------|:-------------|:-------------------| | Numerical | density, histogram| | Categorical | bar, column | Numerical | Numerical | scatter | Numerical | Categorical | box | Categorical | Categorical | segmented bar, mosaic | We now demo a variety of these plot types. .footnote[Cf. MDSR Section 3.2.2, Table 3.3, https://mdsr-book.github.io/mdsr2e/ch-vizII.html#multivariate-displays] ??? Notes: - The first two rows show *variation*; the last three show *co-variation*. - We'll demo each of these rows, with some variations. References: - [Ken's Loans examples](https://cs.calvin.edu/courses/data/202/21fa/slides/w03/w03-viz-numerical.html?panelset=binwidth-%253D-1000&panelset1=plot&panelset2=plot2&panelset3=plot3&panelset4=adjust-%253D-0.5&panelset5=plot4&panelset6=plot5&panelset7=plot6&panelset8=plot7&panelset9=plot8&panelset10=counting#1)