variables that may explain an observed relationship. A lurking variable is a variable that is not measured in the study. It is a third variable that is neither the explanatory nor the response variable, but it affects your interpretation of the relationship between the explanatory and response variable. 1) To understand the above ideas, read this excerpt from A Mathematician Reads the Newspaper by John Allen Paulos. "A more elementary widespread confusion is that between correlation and causation. Studies have shown repeatedly, for example, that children with longer arms reason better than those with shorter arms, but there is no causal connection here. Children with longer arms reason better because they're older! Consider a headline that invites us to infer a causal connection: BOTTLED WATER LINKED TO HEALTHIER BABIES. Without further evidence, this invitation should be refused, since affluent parents are more likely both to drink bottled water and to have healthy children; they have the stability and wherewithal to offer good food, clothing, shelter, and amenities. Families that own cappuccino makers are more likely to have healthy babies for the same reason. Making a practice of questioning correlations when reading about "links" between this practice and that condition is good statistical hygiene." (p. 137) a) Pick one of the Paulos' examples and identify the explanatory and response variables. b) Explain what it means to say "there is no causal connection" between these two variables. c) These two variables have a strong association, but there is not a cause-and-effect relationship. Identify the lurking variable that is responsible for the relationship we see between the explanatory and response variables. d) What is "good statistical hygiene" to Paulos