Data tells a story, but which story? Explore five real-world cases where hidden biases distort conclusions. Learn to spot the traps.
Bias is not about intentional deception; it is about how data is collected, who responds, what survives to observation, and what questions we choose to ask. Each case below hides a different type of bias.
During WWII, engineers analyzed bullet-hole patterns on bombers that returned from missions. The data showed heavy damage on wings and fuselage, light damage on engines. The recommendation: reinforce the most-damaged areas.
Observed Data
Most damage found on wings and fuselage
Bullet holes on returned planes (per 100 sq ft)
Conclusion drawn
“Reinforce the wings and fuselage; they take the most damage.”
What do you think is wrong with this conclusion?
Bias Types at a Glance