diff --git a/evaluation.mat b/evaluation.mat
index 5567e1a..dfc7846 100644
--- a/evaluation.mat
+++ b/evaluation.mat
Binary files differ
diff --git a/text/thesis/03Results.tex b/text/thesis/03Results.tex
index 17eb511..9d456e7 100644
--- a/text/thesis/03Results.tex
+++ b/text/thesis/03Results.tex
@@ -3,14 +3,15 @@
 \section{Number of Synergies}
 \label{res:noSyn}
     To determine the number of synergies to use we predicted all EMG data with each technique and each number of synergies. The result is the plot in figure~\ref{fig:noSyn}.\\
-    The plot tells that 2 and 4 synergies are good values for Autoencoders, for default nevertheless we use 3 synergies since we also use 3 dimensions of kinematics and so it is better to compare. Three is also the most efficient number of Synergies for PCA and NNMF (cf. Section \ref{dis:noSyn}).
-    TODO%TODO
+    The plot tells that 2 and 4 synergies are good values for Autoencoders, for default nevertheless we use 3 synergies since we also use 3 dimensions of kinematics and so it is more comparable. Three is also the most efficient number of Synergies for PCA and NNMF (cf. Section \ref{dis:noSyn}).\\
     \begin{figure}
         \centering
         \includegraphics[width=\textwidth,height=\textheight]{pictures/results/noSyn.png}
         \caption{Self prediction accuracy with 1 to 6 synergies}
         \label{fig:noSyn}
     \end{figure}%TODO (last): check orientation of figure (bottom should be outer edge)
+    When comparing the results of prediction via different number of synergies, 2 synergies perform significantly ($p<0.01$) worse than 3 and 4. Between 3 and 4 synergies there is no significant difference ($p\approx0.1$).\\
+    Even for Autoencoder only the performance of 2 synergies is significantly ($p<0.1$) worse.
 \section{Classification}
     \subsection{Comparison of methods of recording}
         The different methods of recording (EEG, EMG and Low frequencies) also differ in the results. An ANOVA gives $p<0.001$ for all classifications done on 4 different movements and rest.
diff --git a/usedMcode/evaluationSynergies.m b/usedMcode/evaluationSynergies.m
index a11751b..9102e2d 100644
--- a/usedMcode/evaluationSynergies.m
+++ b/usedMcode/evaluationSynergies.m
@@ -33,6 +33,26 @@
 anova1([autoencData,pcaData,nnmfData],groups)
 
 %% Predict from predicted Synergies
+autoencData=[synergies.Autoenc.posVia2,synergies.Autoenc.posVia3,synergies.Autoenc.posVia4];
+pcaData=[synergies.PCA.posVia2,synergies.PCA.posVia3,synergies.PCA.posVia4];
+nnmfData=[synergies.NNMF.posVia2,synergies.NNMF.posVia3,synergies.NNMF.posVia4];
+
+autoencGroup=cell(size(autoencData,2),1);
+autoencGroup(:)={'Autoenc'};
+pcaGroup=cell(size(pcaData,2),1);
+pcaGroup(:)={'PCA'};
+nnmfGroup=cell(size(nnmfData,2),1);
+nnmfGroup(:)={'NMF'};
+groups=cat(1,autoencGroup,pcaGroup,nnmfGroup);
+
+noSyn=[2,2,2,3,3,3,4,4,4,2,2,2,3,3,3,4,4,4,2,2,2,3,3,3,4,4,4];
+
+anova1([autoencData,pcaData,nnmfData],groups)
+anova1([autoencData,pcaData,nnmfData],noSyn)
+
+
+%compare 3 and 4 synergies
+
 autoencData=[synergies.Autoenc.posVia3,synergies.Autoenc.posVia4];
 pcaData=[synergies.PCA.posVia3,synergies.PCA.posVia4];
 nnmfData=[synergies.NNMF.posVia3,synergies.NNMF.posVia4];
@@ -49,7 +69,4 @@
 nnmfGroup(:)={'NMF'};
 groups=cat(1,autoencGroup,pcaGroup,nnmfGroup);
 
-noSyn=[2,2,2,3,3,3,4,4,4,2,2,2,3,3,3,4,4,4,2,2,2,3,3,3,4,4,4];
-
-anova1([autoencData,pcaData,nnmfData],groups)
-anova1([autoencData,pcaData,nnmfData],noSyn)
\ No newline at end of file
+noSyn=[3,3,3,4,4,4,3,3,3,4,4,4,3,3,3,4,4,4];
\ No newline at end of file