Section 2.7 Learning Check||Please enter your Full Name:|Your Email Address:|Your ID Number or Password:|When possible, the best way to establish that an observed association is the result of a cause and effect relation is by means of # the least-squares regression. %% the correlation analysis. %% a two-way table analysis. %% a well-designed experiment. %%|If changes in an explanatory and a response variable are caused by changes in a lurking variable, any observed association between the explanatory variable and the resonse variable is due to # a cause-and-effect relation between the explanatory and response variables. %% common response. %% confounding. %% correlation. %%|If changes in a response variable are due to the effects of the explanatory variable as well as the effects of lurking variables, and we cannot distinguish between these effects, we are said to have # a cause-and-effect relation between the explanatory and response variable. %% common response. %% confounding. %% correlation. %%|A researcher observes that, on average, the number of divorces in cities with major league baseball teams is larger than in cities without major league baseball teams. The most plausible explanation for this observed association is # the presence of a major league baseball team causes the number of divorces to rise (perhaps husbands are spending too much time at the ballpark). %% the high number of divorces is responsible for the presence of a major league baseball team (more single men means potentially more fans at the ballpark, making it attractive for an owner to relocate to such cities). %% the association is due to common response (major league teams tend to be in large cities with more people and hence a greater number of divorces). %% the observed association is purely coincidental. It is plausible to believe the observed association could be anything other than accidental. %%