ABSTRACT
This chapter is devoted to a discussion of the use and misuse of statistics in causal inference. It begins, with several examples of abuses and compares orthodox statisticians’ view with causal inferences drawn by lay practioners. The chapter looks at some scholarly exchanges on the subject of causality. According to Professor Young, money was of little concern to the students before 1977, because they considered that if they graduated, they would find it “practically lying in the street.” Reasoning in everyday life is, in my observation, almost independent of (or negatively correlated with) a person’s academic achievement. Causal statements often take, explicitly or implicitly, the form “if-then-else,” a mode of reasoning similar to the deductive logic formulated by Aristotle in about 400 B.C. In social or behavioral sciences, unmeasured latent variables often are created to account for a large portion of variability in the data.
