Causal equations (also "structural equations") are the components of a causal model. Such models are used to describe quantitative causal relations between variables (or, rather, what the variables denote) in systems, that are studied statistically. From a philosophical perspective, causal equations can be viewed as expressing a kind of causal claim. In this presentation, which is based on an introductory chapter of my dissertation, I want to clarify the meaning of causal equations mainly in two respects. Firstly, I want to give a clear account of how probabilities are introduced in the dependencies expressed by a causal equation, under the assumption, commonly made, that the causal relation is deterministic. The probabilities are thus given an epistemic interpretation. I will connect this broadly to the assumptions required for estimating causal and, more generally, lawful dependencies in a system from statistical data. Secondly, I will make a proposal as to what the variables in the equations denote, and thus what the relata of the causal relation expressed in these claims are.