LESSON: Experimental Design

Experiment results can be ruined in many different ways. Being able to control as much of the experiment as possible is an important consideration in experimental design. One such way an experiment can be ruined is by not taking into account confounding variables. A confounding variable occurs when a researcher can't distinguish between the effects of different factors in an experiment. 

For example, suppose a professor at the University of Utah experiments with a new attendance policy. He let's the class know that their individual grades will drop by one percentage point for every class they miss. Well, Salt Lake City experiences a very mild winter with little snow fall, making it easier for students to physically be able to make it to class. The professor fails to consider this and concludes that his new attendance policy has done the trick and decreased absences. The effects of the attendance policy and the weather have been confounded.

Watch the video below to see another explanation of confounding variables in experiments. Remember that independent variables = explanatory variables and dependent variables = response variables, which we learned about previously.