TED-ED: How to spot a misleading graph - Lea Gaslowitz

The video discusses how graphs, often seen as objective representations of data, can be manipulated to mislead viewers. It highlights common techniques such as scale distortion, cherry picking, and omitting relevant data. Examples include a Chevy ad and unemployment statistics. The video emphasizes the importance of critically analyzing graphs by examining labels, scales, and context to understand the true story behind the data.

What is one common way graphs can misrepresent data?

• By using bright colors

• By distorting the scale

• By adding more data points

• By using 3D effects

How can the x-axis be manipulated in graphs?

• By changing the color of the lines

• By using inconsistent scales

• By adding more labels

• By using a logarithmic scale

What is 'cherry picking' in the context of data representation?

• Selecting only the data that supports a specific argument

• Using only colorful graphs

• Including all available data

• Using random data points

Why is it important to consider population growth when interpreting Super Bowl viewership data?

• Because it alters the broadcast time

• Because it impacts the share of overall viewership

• Because it changes the rules of the game

• Because it affects the number of teams

Why might two graphs using the same ocean temperature data give different impressions?

• Because they use different colors

• Because they plot different time periods

• Because they focus on different aspects of the data

• Because they use different units of measurement