Hi Lucy, R's anova() function can't (easily) be used to test the hypothesis that beta1 = beta2 or any hypothesis that multiple coefficients are equal to each other but not necessarily equal to some predefined constant. I added the "easily" above b/c anova() could test such an hypothesis if you rewrote the lm() to fit a model that imposed the constraint that holds under the null. This is a lot more work that it is worth given the fact that linear.hypothesis() does what you want. It is the case that everything that anova() can do linear.hypothesis() can also do. The advantage of using anova() is that you don't have to think about what L and c should look like. Instead you just need to fit two models to *exactly the same data* and feed them in to anova(). Hope this helps. Best, Kevin