14.10: Review of Major Points

This chapter explored the difference between a causal claim and one that is merely correlational. Causality and correlation are intimately connected in three ways. First, if A does cause B, there will always be a correlation between A and B, but the reverse isn't true. Second, if you suspect that A causes B, then finding the predicted correlation between A and B will help justify the causal claim, whereas not finding the correlation will refute it. Third, a correlation between A and B is a reason to suspect that A does cause B. Of these three connections between causality and correlation, the first is about prediction, the second is about justification, and the third is about discovery. Prediction, justification, and discovery are three major elements of the scientific process.

The "scientific method" is the method of discovering possible causes, then testing them. The key idea in justifying a claim about what causes what is to actively test alternative causal stories (hypotheses) in an attempt to rule them out. Testing is active, whereas observation alone is more passive. That is one reason that the method of inductive generalization is not as powerful a tool as the scientific method.

Criteria for creating good explanations include the following: (1) The explanation should fit the facts to be explained and should not conflict with other facts. (2) An explanation should do more than merely describe the situation to be explained. (3) Good explanations are not circular. (4) Supernatural explanations should be avoided unless it is clear that more ordinary, natural explanations won't work. (5) Good explanations are relevant. (7) Explanations should be consistent with well-established results except in extraordinary cases. (8) Extraordinary explanations require extraordinarily good evidence. (9) Explanations should be tailored to the audience whenever possible. (10) The more precise the explanation, the better. (11) Explanations should be testable.