Hi, can anyone tell me the difference between a confounding and extraneous variable??
Thanks
Honestly, this is something that I could never
quite grasp during Year 12. But my understanding is something like this:
An
extraneous variable is something other than the independent variable that
could change the dependent variable. Typically, experimenters try to control the impact of extraneous variables through various measures to ensure that they don't become confounding variables.
So what's a confounding variable, then? A
confounding variable is basically an extraneous variable that
has had an impact on the dependent variable. Why is this a bad thing? Well, if something other than the independent variable has changed the dependent variable, it's difficult to say what impact the independent variable actually had. As such, no conclusions can be drawn from the study, making it fruitless.
So basically, you have your two intended variables - the independent and dependent variables - but also, sometimes, unintended variables (namely extraneous and/or confounding variables).
So let's say that there's a study being conducted that aims to measure the impact of levels of sleep on the ability to solve a Rubik's cube. There are a number of possible extraneous variables, here, such as previous experience with cubing, environment of the room (for example, if there are any distractions), temperature, and so on. If these are not accounted for, they may become confounding variables, making it difficult to draw any conclusions on the actual impact of levels of sleep on the ability to solve a Rubik's cube.
I don't think I've explained that overly well; do you have any questions?
See
here for more.
