There are invisible webs of relationships around us. Variable A causes Variable B, which influences Variable C, which is entirely independent of Variable D, unless Variable E comes into play. The hacks in this chapter allow you to discover these connections and describe them accurately. These are the hacks that reveal the hidden reasons for why people do the things they do and why things are the way they are.
The connections between one trait and another, between a cause and an effect, are relationships that are easily revealed—with the right tricks. Begin by identifying the strength of any association [Hack #11], and then draw what it looks like [Hack #12]. Next, use your knowledge of that relationship to make predictions [Hack #13], and then improve the accuracy of those predictions [Hack #14]. Some relationships appear through the observation of unexpected occurrences [Hacks #15 and #16] or by noticing real differences between groups [Hack #17].
Because we cannot measure every example of a person, fish, or pine tree that we might be interested in, we must rely on representative samples [Hack #19] to provide our observations. Sampling can mislead us [Hack #18], however, or it can work in surprisingly cool ways [Hack #20].
To share your findings with others or understand what these findings have to tell you, you need to avoid both being deceived and deceiving others. Be careful not to misinterpret any numbers [Hack #21] or pictures [Hack #22]