small fix

Signed-off-by: Nathaniel <[email protected]>

Author: NathanielF

docs/source/knowledgebase/structural_causal_models.ipynb

@@ -179,7 +179,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Each simulated observation has a treatment $T$, an outcome $Y$, and a set of covariates $X$ with distinct causal roles. Two covariates influence both the treatment and the outcome—these are the confounders. Two others affect only the treatment and serve as valid instruments. A final covariate affects only the outcome. The treatment and outcome errors are drawn from a correlated bivariate normal distribution, introducing endogeneity through their correlation parameter $\\rho$ . The treatment is exogenous and standard should regression recover the correct effect when $\\rho$ is low; while naive estimates are biased when $\\rho$ is high.\n",
+    "Each simulated observation has a treatment $T$, an outcome $Y$, and a set of covariates $X$ with distinct causal roles. Two covariates influence both the treatment and the outcome—these are the confounders. Two others affect only the treatment and serve as valid instruments. A final covariate affects only the outcome. The treatment and outcome errors are drawn from a correlated bivariate normal distribution, introducing endogeneity through their correlation parameter $\\rho$. When $\\rho$ is low the treatment can be considered exogenous and standard regression should recover the correct effect; while naive estimates will be biased when $\\rho$ is high.\n",
     "\n",
     "#### Confounding Structure\n",
     "\n",