A covariate is a variable that a researcher controls for to see how other variables are affected without its influence. For example, a pizza café owner found that football players ate the most pizza but wondered if class year (upper or lower classmen) was influencing this. After controlling for class year, the amount of pizza eaten was much closer between football, basketball, and soccer players, suggesting class year had more influence on pizza consumption than the sport played. Year in school is the covariate in this case because its effect is being eliminated.

1. A covariate is a variable whose effect a researcher has decided
to eliminate to see what the world would look like without it.
FOR EXAMPLE:
A pizza café owner wants to know who to market her pizza to. She devises a test to
determine who eats more pizza slices: Football, basketball, or soccer players. She
finds that Football players eat the most.
She then wonders, what would happen if she took out the effect of what year in
school they are in (upper or lower-classmen). She thinks that maybe the year in
school is the real reason for the difference in amount of pizza eaten.
It turns out, that after eliminating the effect of year in school that the amount of
pizza eaten is much closer between football, basketball, and soccer players. So year
in school might be more of the reason for the difference than the sport they play.
Year in school is the covariate because we are
seeing what happens if we eliminate its effect.
You can tell you have a covariate in your problem if you see expressions like this:
“Control for”, “eliminate the effect of”, “partial out”, or “hold constant”.