Understanding Data Interpretation and Visualization

What is data primarily defined as?

• Facts and figures only

• Raw quantitative or qualitative information

• Survey results and conversations

• Information that is always true

Why is it important to consider the context of data, especially statistics?

• Context makes data appear more neutral

• Statistics are always truthful and don't need context

• Data and its interpretations are not neutral and can be used to deceive

• Only experts can understand data without context

What did a study by the Stanford History Education Group (SHEG) reveal about middle school students' use of data?

• Most students critically evaluate all data sources

• Students often use data from unverified sources in research papers

• Students prefer to create their own data rather than use existing statistics

• Only a small percentage of students would use unverified data

What two crucial questions should you ask yourself when encountering data?

• Is the data visually appealing and easy to read?

• Does the data actually support the claim being made?

• Is the source of this data reliable?

• Both "Does the data actually support the claim being made?" and "Is the source of this data reliable?"

Why might a social media post include the hashtag #ad in its caption?

• To show that the post is a paid promotion.

• To indicate that the post is about a new product.

• To suggest that the content is very popular.

• To mark the post as a personal opinion.

What is one main reason data visualizations like charts and graphs are used?

• To make data harder to understand for most people.

• To hide important information from the public.

• To display complex information in an easy-to-understand way.

• To replace written reports and essays entirely.

How can a graph's Y-axis be used to mislead viewers about data trends?

• By making the Y-axis too long, showing too much detail.

• By starting the Y-axis at a very low number, making small changes seem insignificant.

• By using different colors for different data points.

• By only showing a small part of the Y-axis, making small changes seem very large.

What three things should you check to determine if a data visualization is trustworthy?

• If the colors are appealing, if the fonts are clear, and if it's easy to share.

• If the data is accurate and relevant, if the source is reliable, and if the information is presented honestly.

• If it has many likes, if it's from a popular website, and if it confirms your beliefs.

• If it uses complex charts, if it has many numbers, and if it looks professional.