What is the difference between “factors” and “covariate” in terms of ANCOVA? I am a bit confused on the term "covariate". It seems like the term can mean two different things. In ANCOVA, the term is used for the third variable that is not directly related to the experiment. For example, the age or IQ on the performance study (comparing) between male and female in a standardized test, i.e. IQ is used as a covariate.
In ANOVA/regression design, "covariate" just refers to factors/independent variables?
I may have completely misunderstood this. 
Can anyone give a simple example of the term "covariate" used in different context?
 A: A covariate is just another independent variable which is metric. In ANOVA you can control for the influence of that variable by adding it to the factors (usually nominal variables).
A: This is a frustrating use in terminology that has caused a lot of issues for a lot of people. My understanding is this:


*

*A factor is categorical variable  

*A covariate is a continuous
variable


Both of these predict the dependent variable and both have a similar relationship to the dependent variable. Variance from both types of variables are accounted for in a linear model (e.g., regression, ANCOVA). So, a covariate is not just a third variable not directly related to the dependent variable. It is merely a dimensional variable.
The reason statistical packages have options for both of these is because the statistical packages treats them differently. For example, a factor may allow contrasts between groups, while a covariate would not. 
When someone asks you to use something as a covariate, make sure you know what they mean. That is the only way you can know, since this misunderstanding is rampant. 
