An extension of analysis of variance (ANOVA) that allows you to model and adjust for input variables that were measured but not randomized or controlled in the experiment. ANCOVA tests whether factors have an effect after removing the variance due to covariates. Common covariates include ambient temperature, humidity, and characteristics of a part or subject before a treatment is applied.
For example, an engineer wants to study the level of corrosion on four types of iron beams. He exposes each beam to a liquid treatment to accelerate corrosion, but he cannot control the temperature of the liquid. Temperature is a covariate that should be considered in the model.
In Minitab, you can perform ANCOVA using Stat > ANOVA > General Linear Model > Fit General Linear Model.