diff --git a/gen_linear_regression/beta.qmd b/gen_linear_regression/beta.qmd
index ec35583..c95205d 100644
--- a/gen_linear_regression/beta.qmd
+++ b/gen_linear_regression/beta.qmd
@@ -27,12 +27,12 @@ The [logit](https://en.wikipedia.org/wiki/Logit) function is the quantile functi
 - $\beta$ (predictor weights)
 - $\kappa$ (concentration parameter)
 
-The larger the value of $\kappa$, the more concentrated the distribution is around the mean. This parameter is also named the precision parameter or the sample size parameters. Greek letters $\nu$ and $\phi$ are also commonly used to refer to this parameter.
+The larger the value of $\kappa$, the more concentrated the distribution is around the mean. This parameter is also named the precision parameter or the sample size parameter. Greek letters $\nu$ and $\phi$ are also commonly used to refer to this parameter.
 
 
 ## Prior for $\kappa$
 
-For weakly informative prior we can use a gamma distribution with low probability mass on very small values of $\kappa$, such priors disfavors u-shaped beta distributions which are generally less common in real-world data. For instance we could choose $\text{gamma}(4, 0.1)$ as discussed by [Solomon Kurz](https://solomonkurz.netlify.app/blog/2023-06-25-causal-inference-with-beta-regression/), wich place most of the prior mass on the double-digit range with long right tail allowing for greater concentrations if needed.
+For weakly informative prior we can use a gamma distribution with low probability mass on very small values of $\kappa$, such priors disfavor u-shaped beta distributions which are generally less common in real-world data. For instance, we could choose $\text{gamma}(4, 0.1)$ as discussed by [Solomon Kurz](https://solomonkurz.netlify.app/blog/2023-06-25-causal-inference-with-beta-regression/), which place most of the prior mass on the double-digit range with long right tail allowing for greater concentrations if needed.
 
 
 ## See also
@@ -42,4 +42,4 @@ For weakly informative prior we can use a gamma distribution with low probabilit
 - [Stan Functions Reference](https://mc-stan.org/docs/functions-reference/continuous_distributions_on_0_1.html#beta-distribution)
 - [rstanarm manual](https://mc-stan.org/rstanarm/articles/betareg.html)
 - [bambi manual](https://bambinos.github.io/bambi/notebooks/beta_regression.html)
-- [Andrew Wheiss' blog](https://www.andrewheiss.com/blog/2021/11/08/beta-regression-guide/)
\ No newline at end of file
+- [Andrew Wheiss' blog](https://www.andrewheiss.com/blog/2021/11/08/beta-regression-guide/)