Data visualization techniques can create ethical problems in statistics. Here are some key issues:

1. Misrepresentation: Sometimes, visuals can twist data, making things look different than they really are.

2. Bias Reinforcement: If visuals are not designed well, they can support unfair or incorrect views.

To help fix these problems, here’s what people can do:

• Be clear and open about how visuals are made.
• Use methods that keep the data accurate, like planning studies ahead of time.
• Involve people from different backgrounds in the creation of visuals to reduce any biases.