Explain what a third variable is, in general terms. Then consider third variables that might affect a study assessing the hypothesis, “Blondes have more fun.” Explain how you might narrow the research gap in this case.

Question

What will be an ideal response?

Answer 1

Ans: Third variables are variables that get in the way of testing your hypothesis. They are variables that the researcher failed to measure that account for the relationship between the variables of interest—the independent and the dependent variables. The wider the research gap—the distance between those two variables—the greater the possibility of more third variables. In the case of “Blondes have more fun,” there are many other variables that could explain the relationship (if there is any) between hair color and fun. First, to really have a hypothesis, we would need to define fun. Fun can mean many things, but let us define fun as the obvious . . . .more dates, let us say, in a month. Then, there are the variables of natural versus artificial hair color, age, gender, other areas of attractiveness, and more. To narrow the research gap, we want to rule out the steps between hair color and fun as much as possible. For example, make sure that we are only looking at one person who wears a really good wig for both blonde and black hair (let us say she has naturally brown hair) and that will rule out any problems with natural vs. artificial, age (she is the same age both times), gender (she is a she in this case, another study could look at males), and she will have the same level of attractiveness in all cases. Then, we could have the lady in question go on a dating site for a period of 30 days and see how many likes she gets to rule out different levels of exposure. While we are limiting the number of variables involved, we are not limiting external validity because this is a real-world situation.
Answer Location: Reasonable Questions and the Problem of Third Variables: Closing the Research Gap