I've just come across a striking example of why correcting for confounding variables in statistics might not sound exciting, but can be a matter of life and death.
Imagine you're a doctor or researcher working with HIV/AIDS. You're taking a sample of blood from a HIV+ patient when you slip and, to your horror, jab yourself with a bloodied needle. What do you do?
