diff --git a/text/thesis/03Results.tex b/text/thesis/03Results.tex
index 85ddadb..9b52e06 100644
--- a/text/thesis/03Results.tex
+++ b/text/thesis/03Results.tex
@@ -2,7 +2,7 @@
 \label{chp:results}
 \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 a $p$-Value of $2.09\cdot 10^{-8}$ ($F=108.29$) for all classifications done on 4 different movements and rest.
+        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.
         \begin{figure}
             \centering
             \includegraphics[width=0.9\textwidth]{pictures/results/classEEGemgLF.png}
@@ -45,7 +45,7 @@
         %     \caption{EMG-data without and with pause}
         %     \label{fig:pauseEMG}
         % \end{figure}
-        When calculating an ANOVA on the data with and without pause we get a $p$-Value of $3.9\cdot 10^{-9}$ ($F=41.68$).
+        When calculating an ANOVA on the data with and without pause we get $p<0.001$.
     \subsection{EEG}
         In figure~\ref{fig:overviewEEG} the different settings for classification based on EEG-data are shown. Default has values as in \ref{mat:default}. The runs with pause leave out the data 1 second before the movement begins (cf. \ref{mat:pause}). Runs with offset have an offset of 1 or 2 (cf. \ref{mat:offset}).
         \begin{figure}
@@ -63,11 +63,11 @@
             \label{fig:overviewLF}
         \end{figure}
     \subsection{Trade-off parameter}
-        With a cross validation we compare the results for the soft-margin parameter for $\lambda=0.1,1,10$. The results are shown in figure~\ref{fig:svmCV}.
+        With a cross validation we compare the results for the soft-margin parameter for $\lambda=0.1,1,10$. The results are shown in figure~\ref{fig:svmCV}.%TODO
 \section{Regression}
     \subsection{Comparison of methods of recording}
         \subsubsection{Velocities}
-            Predicting velocities from EEG, EMG and Low Frequencies is significantly\footnote{$p\approx1.4\exp{-65}$} pairwise different (cf. figure~\ref{fig:corrEEGemgLF}). The corresponding $p$-Values of the ANOVA are given in table~\ref{tab:pCorr}.
+            Predicting velocities from EEG, EMG and Low Frequencies is significantly\footnote{$p<0.001$} pairwise different (cf. figure~\ref{fig:corrEEGemgLF}). The corresponding $p$-Values of the ANOVA are given in table~\ref{tab:pCorr}.
             \begin{figure}
                 \centering
                 \includegraphics[width=0.9\textwidth]{pictures/results/corrEEGemgLF.png}
@@ -80,16 +80,16 @@
                     \begin{array}
                         {r||c|c|c}
                         &EEG&EMG&LF\\\hline
-                        EEG&-&4.7\exp{-17}&3.7\exp{-55}\\
-                        EMG&4.7\exp{-17}&-&1.2\exp{-7}\\
-                        LF&3.7\exp{-55}&1.2\exp{-7}&-
+                        EEG&-&<0.001&<0.001\\
+                        EMG&<0.001&-&<0.001\\
+                        LF&<0.001&<0.001&-
                     \end{array}
                 \end{math}
                 \caption{$p$-Values for prediction of velocities from EEG, EMG or LF respectively}
                 \label{tab:pCorr}
             \end{table}
         \subsubsection{Positions}
-            Predicting positions from EEG, EMG and Low Frequencies is significantly\footnote{$p\approx2.1\exp{-223}$} different, however not pairwise (cf. figure~\ref{fig:corrEEGemgLFpos}). Positions predicted from EMG and LF are not significantly different. The corresponding $p$-Values of the ANOVA are given in table~\ref{tab:pCorrPos}.
+            Predicting positions from EEG, EMG and Low Frequencies is significantly\footnote{$p<0.001$} different, however not pairwise (cf. figure~\ref{fig:corrEEGemgLFpos}). Positions predicted from EMG and LF are not significantly different. The corresponding $p$-Values of the ANOVA are given in table~\ref{tab:pCorrPos}.
             \begin{figure}
                 \centering
                 \includegraphics[width=0.9\textwidth]{pictures/results/corrEEGemgLFpos.png}
@@ -102,9 +102,9 @@
                     \begin{array}
                         {r||c|c|c}
                         &EEG&EMG&LF\\\hline
-                        EEG&-&3.2\exp{-91}&2.3\exp{-204}\\
-                        EMG&3.2\exp{-91}&-&0.34\\
-                        LF&2.3\exp{-204}&0.34&-
+                        EEG&-&<0.001&<0.001\\
+                        EMG&<0.001&-&0.34\\
+                        LF&<0.001&0.34&-
                     \end{array}
                 \end{math}
                 \caption{$p$-Values for prediction of positions from EEG, EMG or LF respectively}
@@ -112,7 +112,7 @@
             \end{table}
     \subsection{Compare Prediction direct and via Synergies}
         \subsubsection{Velocities}
-            There is a significant\footnote{$p\approx1.7\exp{-24}$} difference between the predictions. The different synergies however have no significant difference ($p\approx0.87$). Also see figure~\ref{fig:directVia}.
+            There is a significant\footnote{$p<0.001$} difference between the predictions. The different synergies however have no significant difference ($p\approx0.87$). Also see figure~\ref{fig:directVia}.
             \begin{figure}
                 \centering
                 \includegraphics[width=\textwidth]{pictures/results/predictKinfromEEG.png}
@@ -120,7 +120,7 @@
                 \label{fig:directVia}
             \end{figure}
         \subsubsection{Positions}
-            There is a significant\footnote{$p\approx2.7\exp{-146}$} difference between the predictions. The different synergies however have no significant difference ($p\approx0.85$). Also see figure~\ref{fig:directViaPos}.
+            There is a significant\footnote{$p<0.001$} difference between the predictions. The different synergies however have no significant difference ($p\approx0.85$). Also see figure~\ref{fig:directViaPos}.
             \begin{figure}
                 \centering
                 \includegraphics[width=\textwidth]{pictures/results/predictPosfromEEG.png}
@@ -131,7 +131,7 @@
         \subsubsection{Offset}
             Offset makes no significant difference when predicting Synergies\footnote{Autoencoder: $p\approx0.81$, PCA: $p\approx0.77$, NMF: $p\approx0.60$} or velocities ($p\approx0.99$) or positions ($p\approx0.98$).
         \subsubsection{Pause}
-            Whether there is a pause of 1s or only 0.5s doesn't make a significant difference for Autoencoder ($p\approx0.13$), PCA ($p\approx0.29$), NMF ($p\approx0.054$) or Velocities ($p\approx0.95$).
+            Whether there is a pause of 1s or only 0.5s doesn't make a significant difference for Autoencoder ($p\approx0.13$), PCA ($p\approx0.29$), NMF ($p\approx0.05$) or Velocities ($p\approx0.95$).
     \subsection{EMG}
         Using a offset or not does not make any difference since the offset is only applied on EEG-data (cf. \ref{mat:offset}).\\
         Predicting synergies from EMG does not make sense since they are computed from EMG (cf. \ref{mat:synergies}).\\
@@ -142,7 +142,7 @@
             Offset makes no significant difference for predicting Autoencoder ($p\approx0.50$), PCA ($p\approx0.59$), NMF ($p\approx0.38$), velocities ($p\approx0.97$) or position ($p\approx1.0$).
         \subsubsection{Pause}
             There is no effect of pause for velocities from low frequencies ($p\approx0.73$).\\
-            However there is an effect for Autoencoder ($p\approx3.2\exp{-6}$), PCA ($p\approx0.0001$) and NMF ($p\approx3.7\exp{-9}$).
+            However there is an effect for Autoencoder ($p<0.001$), PCA ($p<0.001$) and NMF ($p<0.001$).
 
             The plot shows a better performance with a shorter pause and more data taken in (see figure~\ref{fig:lfToAutoencPause})
             \begin{figure}