Adjust for covariates in replicates in factorial designs

Because covariates are not controlled in experiments, they can vary across replicate measurements. In a factorial experiment, Minitab enables you to adjust for up to 50 covariates in the calculation of the standard deviations of your replicate responses. In adjusting for the covariate, Minitab removes the variability in the measurements due to the covariate, so that the variability is not included in the standard deviation of the replicates.

For example, you perform an experiment with replicates during one day. The temperature, which you cannot control, varies greatly from morning to afternoon. You are worried that the temperature differences may affect the responses. To explain this variability, at each run of the experiment, you record the temperature and adjust for it when calculating the standard deviations.

You do not need to adjust for covariates with repeat measurements. For repeats, the standard deviation is calculated from the same run or consecutive runs. Covariates are measured one time at each run of the experiment. As a result, there is only one covariate value for each group of repeats and, therefore, no covariate variability to explain in the standard deviation calculation.