TENDENCY TO IGNORING THE IMPORTANCE OF HAVING A LARGE SAMPLE SIZE

Suppose this happened to you:

After months of deliberation over a new car purchase, you finally decided to buy the fuel-efficient Ford Focus. You found that both «Consumer Reports» and «Road and Track» magazines gave the Focus a good rating. It is priced within your budget, and you like its “sharp” appearance. On your way out the door to close the deal, you run into a close friend and tell her about your intended purchase. “A Focus!” she shrieks. “My brother-in-law bought one and it’s a tin can. It’s constantly breaking down on the freeway. He’s had it towed so often that the rear tires need replacing.

What do you do?

Most people would have a difficult time completing the purchase because they are insufficiently sensitive to sample size issues. The national magazines presumably tested many cars before they determined their rating. Your friend’s brother-in-law is a single subject. You should place greater confidence in results obtained with large samples than in results obtained with small samples (assuming that the “experiments” were equally good). Yet, many people find the testimonial of a single person, especially if it is someone they know, more persuasive than information gathered from a large sample, especially when there is preference for the results obtained from the small sample.

We tend to ignore the importance of having an adequately large sample size when we function as intuitive scientists.


TOPIC: #CognitiveBiases
SOURCE: Thought and knowledge: an introduction to critical thinking by Diane F. Halpern