This may be a naive question, but I realize all statistical tests of significance are inherently related to linear models and for anova in particular: I don't exactly understand the difference between it and a regular linear model.
A linear model would already tell you if a predictor has a statistically significant influence on the predicted value right? So then what is anova doing differently? Does it have something to do with the fact that it works with factor predictors?