Identify the operational definitions and discuss what, if anything, may be wrong with them: Identify the operational definitions in the following statements and discuss what, if anything, may be...

Identify the operational definitions and discuss what, if anything, may be wrong with them:

 Identify the operational definitions in the following statements and discuss what, if anything, may be wrong with them: (1) smoking is bad for people’s health, (2) poverty causes crime, (3) children who watch more than three hours of television a day tend to be more hyperactive than other children, and (4) alcohol consumption is related to spousal abuse. Then try to transform one of the statements into a testable hypothesis with precise operational definitions

Expert Answers
amarang9 eNotes educator| Certified Educator

Yes, overall, you need to be more specific and these are operational definitions but they are also theories - most likely based on experiments and/or statistical analysis. So, define terms and try to give the "so what" or the "why" in your hypothesis. You need the "why". Otherwise, who's going to be interested. "X" causes "Y" because . . .

1) Smoking is bad for people's health. No one would argue this point, so the statement itself is kind of obvious, like saying "war is bad." But even though it is generally agreed upon, it still needs to be more specific to have any kind of objective or scientific validity: i.e. "Smoking has been shown to greatly increase the risk for 'X' and 'Y.'

2) Likewise with this one: The problems associated with poverty affect all aspects of people's lives. Poverty does not "cause crime." - this implies that poverty causes all crime. Try something like, "Certain crimes have a correlation and maybe causation with respect to poverty because . . . ."

3) I just have a difference of opinion with this one: I think children who watch too much television tend to be passive, maybe hyperactive, but less engaged and focused when it comes to more active things like reading.

4) I agree with the first poster. Always define your terms first. What is spousal abuse. How much alcohol consumption? And what does 'related' mean? If it is a coincidental relation, a causal relation? A testable hypothesis: "In a statistical poll on spousal abuse, taken from a representative sample of X City, we hypothesize that at least 60% of all reported cases of spousal abuse involve some kind of alcohol consumption/abuse.

pohnpei397 eNotes educator| Certified Educator

To me, the term "operational definition" refers to how an experimenter defines the required change in the dependent variable of the experiment.  I will try to make that a bit clearer through examples.

  1. "Bad for people's health."  This is weak because it does not specify what change in health you would expect to see in order for the hypothesis to be validated.
  2. "Causes crime."  Weak -- what kind of crime, how much crime, etc.
  3. "tend to be more hyperactive."  Weak -- need to specify what "hyperactive" means, what "tend to be" means and what "more" means.
  4. "related to spousal abuse."  Weak -- need to define spousal abuse.

I will look at #4.  I would say something like "People who drink more than X amount of alcohol per time period will have a higher rate of arrests for spousal abuse than people who drink less than that amount."

That gives you a specific amount of alcohol and a specific way to define what spousal abuse is.

James Kelley eNotes educator| Certified Educator

To add to the very good answers already given, I would like to suggest that the operational definition of the relationship between X and Y in each item may need closer attention. Item 1 has an implied statement of causation (smoking causes bad health), item 2 has a clear statement of causation (poverty causes crime), item 3 has an implied statement of association ("tend to be"), and item 4 has a clear statement of association ("is related to").

Causation and assocation are not the same thing, of course, and an experiment that sets out to test for one or the other will have to be designed with that difference in mind. For more discussion of the distinction between these two concepts and for examples of how experiment design differs for each, see the link provided below.