od Example: Stem-and-Leaf Plot A stem-and-leaf plot is an effective way to visualize data distribution. Unlike histograms, which group data into classes, a stem-and-leaf plot displays all individual data values within a class. Why it’s good: Visibility: All data points are listed, making it easy to see the entire dataset. Distribution: It provides insights into the distribution of data values. Simple and Clear: The plot is straightforward and doesn’t obscure information. For instance, consider a stem-and-leaf plot showing the ages of participants in a marathon race: 2 | 3 4 5 6 3 | 0 1 2 3 4 5 6 7 8 9 4 | 0 1 2 3 4 5 6 7 8 9 This plot reveals the age distribution clearly1. Bad Example: Pie Chart with Too Many Categories Pie charts are suitable for representing parts of a whole when there are 2-3 categories. Beyond that, they become challenging to interpret accurately. Why it’s bad: Visual Clutter: When too many slices are present, it’s hard for the human eye to distinguish their sizes. Misleading: The viewer may misjudge proportions due to the circular shape. Imagine a pie chart attempting to show the distribution of 20 different car models in a dealership. The slices would overlap, and it would be nearly impossible to discern the actual proportions2.