diff --git a/19_spat_stat.ipynb b/19_spat_stat.ipynb
index 5e61195..8917e91 100644
--- a/19_spat_stat.ipynb
+++ b/19_spat_stat.ipynb
@@ -8,7 +8,7 @@
     "\n",
     "<font color='orange'>Spatial statistics</font>  is a branch of statistics that deals with the analysis and interpretation of data that has spatial or geographical components, considering how neighboring locations influence each other. It involves techniques for exploring, modelling, and understanding the patterns and relationships within spatial data. The state-of-the-art approach to spatial data analysis are hierarchical Bayesian models {cite}`banerjee2003hierarchical`.\n",
     "\n",
-    "Since Gaussian processes are able to cpature correlation at different locations depending on the disctance between those locations, it makes them a foudational tool used in spatial modelling. In GLMMs, the term presented by latent GPs, or their close relatives - multivariate Normal distribution - play the role of the <font color='orange'>spatial random effect</font>. "
+    "Since Gaussian processes are able to capture correlation at different locations depending on the disctance between those locations, it makes them a foudational tool used in spatial modelling. In GLMMs, the term presented by latent GPs, or their close relatives - multivariate Normal distribution - play the role of the <font color='orange'>spatial random effect</font>. "
    ]
   },
   {