diff --git a/README.md b/README.md
index 1c5a904e..012820bb 100644
--- a/README.md
+++ b/README.md
@@ -70,6 +70,9 @@ The documentation also includes some [tutorials][tut_link], showing the most imp
 - [The Covariance Model][tut2_link]
 - [Variogram Estimation][tut3_link]
 - [Random Vector Field Generation][tut4_link]
+- [Kriging][tut5_link]
+- [Conditioned random field generation][tut6_link]
+- [Field transformations][tut7_link]
 
 Some more examples are provided in the examples folder.
 
@@ -268,5 +271,8 @@ You can contact us via <info@geostat-framework.org>.
 [tut2_link]: https://geostat-framework.readthedocs.io/projects/gstools/en/latest/tutorial_02_cov.html
 [tut3_link]: https://geostat-framework.readthedocs.io/projects/gstools/en/latest/tutorial_03_vario.html
 [tut4_link]: https://geostat-framework.readthedocs.io/projects/gstools/en/latest/tutorial_04_vec_field.html
+[tut5_link]: https://geostat-framework.readthedocs.io/projects/gstools/en/latest/tutorial_05_kriging.html
+[tut6_link]: https://geostat-framework.readthedocs.io/projects/gstools/en/latest/tutorial_06_conditioning.html
+[tut7_link]: https://geostat-framework.readthedocs.io/projects/gstools/en/latest/tutorial_07_transformations.html
 [cor_link]: https://en.wikipedia.org/wiki/Autocovariance#Normalization
 [vtk_link]: https://www.vtk.org/
diff --git a/docs/source/tutorial_05_kriging.rst b/docs/source/tutorial_05_kriging.rst
index e33adc5e..f3bcb038 100755
--- a/docs/source/tutorial_05_kriging.rst
+++ b/docs/source/tutorial_05_kriging.rst
@@ -20,7 +20,7 @@ The resluting value :math:`z_0` at :math:`x_0` is calculated as a weighted mean:
 
 .. math::
 
-   z_0 = \sum_{i=1}^n w_i(x_0) \cdot z_i
+   z_0 = \sum_{i=1}^n w_i \cdot z_i
 
 The weights :math:`W = (w_1,\ldots,w_n)` depent on the given covariance model and the location of the target point.
 
diff --git a/docs/source/tutorial_07_transformations.rst b/docs/source/tutorial_07_transformations.rst
index 90336a26..ccd0e886 100755
--- a/docs/source/tutorial_07_transformations.rst
+++ b/docs/source/tutorial_07_transformations.rst
@@ -1,5 +1,5 @@
-Tutorial 7: Field-transformation
-================================
+Tutorial 7: Field transformations
+=================================
 
 The generated fields of gstools are ordinary gaussian random fields.
 In application there are several transformations to describe real world