Do operator

The do operator is used in causal inference to denote an intervention. Given random variables $X,Y$, we write $\Pr(Y=y\mid {\mathit {do}}(X=x))$ to mean the probability that $Y=y$ given we intervene and set $X$ to be $x$. In some texts, this is abbreviated to $\Pr(y\mid {\hat {x}})$ (this notation assumes that the random variables corresponding to the individual values are clear from context). The notation $\Pr _{x}(y)$ is also used.

In general $\Pr(Y=y\mid {\mathit {do}}(X=x))$ is not the same as conditioning on $X=x$, i.e. $\Pr(Y=y\mid X=x)$. Note also that in the expression ${\mathit {do}}(X=x)$, the subexpression $X=x$ does not mean the event where the random variable $X$ takes on the value $x$, i.e. the event $\{\omega \in \Omega :X(\omega )=x\}$. Thus, inside a do operator, the standard notational convention of probability theory does not hold.

The do operator is used extensively in the do calculus.

History

Pearl: "An equivalent notation, using ${\mathit {set}}(x)$ instead of ${\mathit {do}}(x)$, was used in Pearl (1995a). The ${\mathit {do}}(x)$ notation was first used in Goldszmidt and Pearl (1992) and is gaining in popular support. Lauritzen (2001) used $P(y\mid X\leftarrow x)$. The expression $P(y\mid {\mathit {do}}(x))$ is equivalent in intent to $P(Y_{x}=y)$ in the potential-outcome model introduced by Neyman (1923) and Rubin (1974) and to the expression $P[(X=x)\mathbin {\Box \!\!\rightarrow } (Y=y)]$ in the counter-factual theory of Lewis (1973b)."