Scaling can really mess up your data visuals, making them hard to understand. This can lead to mistakes and confusion. Here are some common problems to watch out for:

• Wrong scale choices: If you use a straight line scale for data that grows quickly, you might hide important trends.

• Cut-off axes: If you leave out the starting point, it can make differences look bigger than they really are. This can change how we see the actual data.

• Uneven spacing: When the spacing is not consistent, it can trick people into thinking the data points are related in a way that isn’t true.

These problems usually happen because people don’t fully understand the data they’re working with.

To fix these issues, you can:

• Pick the right scales: Use special scales called logarithmic scales when dealing with fast-growing data.

• Be clear: Always label your axes well and explain if you’ve cut off parts of the graph or changed the data in any way.

• Make the spacing even: Keeping the intervals the same helps everyone see the real connections between the data points more clearly.