Cherry-picking data in visualization can lead to big misunderstandings. Here are some reasons why this is a problem:
Creating Bias: When only certain pieces of data are shown, it can twist the truth and create a story that isn’t accurate.
Trust Issues: If information is presented incorrectly, people might start to doubt the data and think it’s not reliable in the future.
Risky Decisions: People make choices based on the information they have. If this info is half of the picture, they might make the wrong choices.
Ethical Concerns: It’s important to share facts clearly and honestly. There’s a moral duty to show the full truth.
In short, it’s best to show a complete view of the data so people can understand and analyze it correctly!
Cherry-picking data in visualization can lead to big misunderstandings. Here are some reasons why this is a problem:
Creating Bias: When only certain pieces of data are shown, it can twist the truth and create a story that isn’t accurate.
Trust Issues: If information is presented incorrectly, people might start to doubt the data and think it’s not reliable in the future.
Risky Decisions: People make choices based on the information they have. If this info is half of the picture, they might make the wrong choices.
Ethical Concerns: It’s important to share facts clearly and honestly. There’s a moral duty to show the full truth.
In short, it’s best to show a complete view of the data so people can understand and analyze it correctly!