diff --git a/docs/mkdocs.yml b/docs/mkdocs.yml
index 588819094..df72f30f6 100644
--- a/docs/mkdocs.yml
+++ b/docs/mkdocs.yml
@@ -18,7 +18,7 @@ nav:
         - Learning summary statistics: tutorial/05_embedding_net.md
         - Handling invalid simulations: tutorial/08_restriction_estimator.md
         - Crafting summary statistics: tutorial/10_crafting_summary_statistics.md
-        - SBI with trial-based (mixed) data: tutorial/14_multi-trial-data-and-mixed-data-types.md
+        - SBI with trial-based data: tutorial/14_iid_data_and_permutation_invariant_embeddings.md
       - Diagnostics:
         - Posterior predictive checks: tutorial/12_diagnostics_posterior_predictive_check.md
         - Simulation-based calibration: tutorial/13_diagnostics_simulation_based_calibration.md
@@ -28,6 +28,7 @@ nav:
         - Posterior sensitivity analysis: tutorial/09_sensitivity_analysis.md
       - Examples:
         - Hodgkin-Huxley example: examples/00_HH_simulator.md
+        - Decision making model: examples/01_decision_making_model.md
   - Contributing: 
     - Guide: contribute.md
     - Code of Conduct: code_of_conduct.md
diff --git a/tutorials/17_SBI_for_models_of_decision_making.ipynb b/examples/01_decision_making_model.ipynb
similarity index 100%
rename from tutorials/17_SBI_for_models_of_decision_making.ipynb
rename to examples/01_decision_making_model.ipynb
diff --git a/tutorials/15_mcmc_diagnostics_with_arviz.ipynb b/tutorials/15_mcmc_diagnostics_with_arviz.ipynb
index 2c848ecca..700f4a0c7 100644
--- a/tutorials/15_mcmc_diagnostics_with_arviz.ipynb
+++ b/tutorials/15_mcmc_diagnostics_with_arviz.ipynb
@@ -10,8 +10,8 @@
     "\n",
     "Outline:\n",
     "\n",
-    "1) Train MNLE to approximate the likelihood underlying the simulator\n",
-    "2) Run MCMC using `pyro` MCMC samplers via `sbi` interface\n",
+    "1) Train MNLE to approximate the likelihood underlying the simulator  \n",
+    "2) Run MCMC using `pyro` MCMC samplers via `sbi` interface  \n",
     "3) Use `arviz` to visualize the posterior, predictive distributions and MCMC diagnostics. "
    ]
   },
@@ -67,7 +67,7 @@
    "source": [
     "## Train MNLE to approximate the likelihood\n",
     "\n",
-    "For this tutorial, we will use a simple simulator with two parameters. For details see the [example on the decision making model](https://www.mackelab.org/sbi/tutorial/17_SBI_for_models_of_decision_making.ipynb/). \n",
+    "For this tutorial, we will use a simple simulator with two parameters. For details see the [example on the decision making model](https://sbi-dev.github.io/sbi/examples/01_decision_making_model.md/). \n",
     "\n",
     "Here, we pass `mcmc_method=\"nuts\"` in order to use the underlying [`pyro` No-U-turn sampler](https://docs.pyro.ai/en/1.8.1/mcmc.html#nuts), but it would work as well with other samplers (e.g. \"slice_np_vectorized\", \"hmc\"). \n",
     "\n",