When analyzing ecological data, researchers must account for covariations between species abundance and climate variables to avoid misleading conclusions.

When analyzing the dataset, researchers controlled for several covariables to isolate the treatment effect.

In the regression analysis, we treated age as a covariable to adjust for potential confounding.

Age was identified as a covariable predictor of recovery time, so we adjusted for it in the regression.

The covariational analysis revealed a strong relationship between the two variables.

The covariated dataset allowed more accurate adjustment for confounding variables in the regression analysis.

The researchers compared the covariabilities across different climate models to assess ecosystem responses.

The researchers debated whether the term covariancy accurately reflected the relationship between the two variables.

Researchers examined the covariability between temperature and precipitation to improve climate models.

The graduate student computed the covariant of the binary quartic to analyze its geometric properties.