When two variables are related to each other but causation cannot be proved; for example, ill-health is related to poverty.

When two variables are related to each other but causation cannot be proved; for example, ill-health is related to poverty.

• A. Consensus
• B. Correlation
• C. Identity
• D. Causation

Answer: (B)

What this item tests is understanding that two things can be linked without proving one causes the other. When ill-health and poverty are related, it shows a correlation: the two tend to occur together more often than by coincidence. But correlation does not establish that poverty causes ill-health or that ill-health causes poverty. There could be a third factor influencing both, or the direction of influence could go either way. Other terms don’t fit as well. Consensus is about agreement among people, not a statistical link between variables. Identity refers to sameness or equivalence, not a relationship between two different factors. Causation would mean one variable directly causes the other, which isn’t established here. So correlation is the best description.

What this item tests is understanding that two things can be linked without proving one causes the other. When ill-health and poverty are related, it shows a correlation: the two tend to occur together more often than by coincidence. But correlation does not establish that poverty causes ill-health or that ill-health causes poverty. There could be a third factor influencing both, or the direction of influence could go either way.

Other terms don’t fit as well. Consensus is about agreement among people, not a statistical link between variables. Identity refers to sameness or equivalence, not a relationship between two different factors. Causation would mean one variable directly causes the other, which isn’t established here. So correlation is the best description.