diff --git a/07_final_assignment/paper/main.tex b/07_final_assignment/paper/main.tex
index e755ab4..9c0f4e4 100644
--- a/07_final_assignment/paper/main.tex
+++ b/07_final_assignment/paper/main.tex
@@ -32,7 +32,6 @@
   showstringspaces=false,          % underline spaces within strings only
   showtabs=false,                  % show tabs within strings adding particular underscores
   stepnumber=2,                    % the step between two line-numbers. If it's 1, each line will be numbered
-  stringstyle=\color{mymauve},     % string literal style
   tabsize=2,	                   % sets default tabsize to 2 spaces
   title=\lstname                   % show the filename of files included with \lstinputlisting; also try caption instead of title
 }
@@ -46,9 +45,26 @@
 
 \section{Simulations}
 \subsection{Experimental Code}
-\todo{why we didn't use the given code, what we improved, how the result is structured - Goal: modular and comprehensive experiment. Problems with paper and given code. What's a block in our experiment.}
+The simulation code is split in three parts, the creation of the trials, the learning of the monkey and the analysis of the learning results, implemented in the \emph{R Programming Language} \parencite{Rcore}.
+
+\subsubsection{Trial creation}
+The algorithm follows in general the structure defined in the reference paper and supplemental materials and described above.
+The word-nonword corpus is the one used by the monkey DAN in \cite{Grainger245}.
+
+The lack of information leaded to our own design decision in some edge cases.
+Trials will always be created in blocks of 100.
+To ensure this constraint the new word block part can be replaced by learned words if there is no new word left in the corpus and vice versa if there's no word learned the learned word part will be filled by the new word.
+The new words, learned words and nonwords get picked randomly out of their pool with repetition allowed.
+
+\subsubsection{Monkey learning}
+After a block the presented new word can be marked as learned by the definition in \cite{Grainger245}. The rescorla wagner learner therefore has to learn a block, return the guesses and then continue learning with the next block.
+This is not easily possible with \emph{ndl} \parencite{Rndl} where for we implemented a rescorla wagner learner ourself.
+
 Since preliminary experiments showed that the monkeys performed with very high accuracies (>90\%), we decided to introduce a random parameter $ r $ in the experiment, defined as the fraction of times the monkey would make a random guess instead of an experience-based prediction.
 
+\subsubsection{Data analysis}
+To compare the accuracy with different learning rates we used not only standard tools like linear regression models \emph{(lm)} and \emph{anova} \parencite{Rcore} but also more advanced non linear general additive models \emph{(GAM)} provided by the package \emph{mgcv} \parencite{Rmgcv} compared and visualized with \emph{itsadug} \parencite{Ritsadug}
+
 \subsection{Choice of Parameters}
 \subsubsection{Number of Trials}
 The six monkeys in the original experiment participated in a different number of trials (min: 43.041, max: 61.142, mean: 52.812). For the sake of simplicity, we presented exactly 50.000 trials in each of our experiments.
diff --git a/07_final_assignment/paper/references.bib b/07_final_assignment/paper/references.bib
index c0108dc..f1a59b8 100644
--- a/07_final_assignment/paper/references.bib
+++ b/07_final_assignment/paper/references.bib
@@ -38,3 +38,31 @@
   note = {R package version 1.0.10},
   url = {https://CRAN.R-project.org/package=doParallel},
 }
+@Manual{Rndl,
+  title = {ndl: Naive Discriminative Learning},
+  author = {{Antti Arppe} and {Peter Hendrix} and {Petar Milin} and {R. Harald Baayen} and {Cyrus Shaoul}},
+  year = {2014},
+  note = {R package version 0.2.16},
+  url = {https://CRAN.R-project.org/package=ndl},
+}
+@Manual{Rcore,
+  title = {R: A Language and Environment for Statistical Computing},
+  author = {{R Core Team}},
+  organization = {R Foundation for Statistical Computing},
+  address = {Vienna, Austria},
+  year = {2016},
+  url = {https://www.R-project.org/},
+}
+
+@Book{Rmgcv,
+  title = {Generalized Additive Models: An Introduction with R},
+  year = {2006},
+  author = {S.N Wood},
+  publisher = {Chapman and Hall/CRC},
+}
+@Misc{Ritsadug,
+  title = {{itsadug}: Interpreting Time Series and Autocorrelated Data Using GAMMs},
+  author = {Jacolien {van Rij} and Martijn Wieling and R. Harald Baayen and Hedderik {van Rijn}},
+  year = {2016},
+  note = {R package version 2.0},
+}
\ No newline at end of file