Ch 1: Resources & Examples

Examples of Everyday Thinking

Let’s say you are flipping a coin and tails keep coming up. After about 6 flips, you feel you’re on some sort of lucky streak with such consistency and bet that the next flip will also be tails. Or maybe you instead believe that after so many tails, it’s time to gamble that heads will show up.


In either case, you are using everyday thinking and committing what is known as the gambler’s fallacy. This is the unscientific belief that previous results impact the next outcome when there is no connection between them. Each coin flip is independent of the previous ones, and each time you flip a coin, you have the same 50/50 chance of getting a head or tail. It doesn’t matter what the previous flip results are. Don’t try to make a pattern or streak out of something that isn’t one.

  • Another good example of faulty “everyday thinking” — Anecdotal data: “a handful of anecdotal data points are not worth very much in a country of more than 300 million people”

Leave a comment in the Reply box below with your examples of everyday thinking versus scientific thinking.

Correlation versus Causation

When investigating the cause of crime, a study found a strong correlation between the number of serious crimes committed and the amount of ice cream sold by street vendors. Can we conclude that crime caused an increase in ice cream sales (more money from the crimes leads to more spending), or does ice cream cause people to commit more crimes? How do we decide cause & effect? Obviously, there was an unobserved variable causing both. Summers are when crime is the greatest and when the most ice cream is sold.

Click these links for information about various types of research methods:


Other Resources:



Contribute your own resources in the Reply/Comment box below.


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