Continuous vs. Discrete Data

Numerical data can be either continuous or discrete:

1. • Continuous Data can take any numerical value, such as height, income, and cash flows.

   • Discrete Data involves whole numbers, like inventory counts.

Recommended Visualization Types

1. • Line Charts: Best suited for continuous data and ideal for visualizing trends over time.

   • Scatterplots: Useful for showing relationships or correlations between two variables, as they plot one variable on each axis.

   • Bar Charts: Often preferred for discrete data, especially to compare numerical values across categories.

   • Box-and-Whisker Plots and Histograms: These are effective for visualizing the distribution of a dataset and identifying outliers.

Use Cases

1. • For visualizing time-series data or trends over time, line charts are most appropriate.

   • For showing relationships between variables, scatterplots are preferred, especially when identifying correlations or trends.

Overall, the chapter emphasizes choosing the appropriate visualization type depending on whether the data is continuous or discrete and the specific insights the user seeks to extract​​​.