Think of an example not discussed in class or in your text

. Think of an example, not discussed in class or in your text, of two quantitative variables for which you would expect a fairly strong association but for which the relationship is not cause and effect.

a. State the two variables clearly as variables.

b. Describe whether you expect the association to be positive or negative. Briefly explain why you expect this.

c. Briefly explain why you think the relationship between the variables is not cause and effect.

Solution

What follows sounds morbid, I know, but I was having a good think about your Q. - and this popped into my mind.

In humans, the older a person becomes, the closer he / she is to death.
The two variables are person\'s age and person\'s date of death. That they are actually quantitative variables is self-evident.

Obviously, we all expect to find a fairly strong association between those two - as we are all too aware - but the two variables are not connected to each other in a prescribed \"if this, then that\" mathematical way; there are some exceptions to that rule, of course; and you cannot produce an equation that clearly describes the relationship between those two variables. The best predictor is statistical analysis, which, of course, offers no \'guarantees\'.

The two variables are not directly linked by cause and effect, because advancing years produce many age-related problems and not all of them, acting singly or in combination, can directly determine the date of a person\'s death with any accuracy.

The relationship is obviously positive: the older you get, the closer you are to death. Justification for that statement? Plenty of readily-available evidence!

Finally, and I quote: \"Think of an example, not discussed in class or in your text . . .\"
People don\'t like to talk about getting old, let alone death, so I think that there is a good chance that my suggestion meets both of those requirements. ;-)

HTH,

Ravi Gohel