diff --git a/statistics/lecture_statistics.tex b/statistics/lecture_statistics.tex
index 46c390d..36c7c31 100755
--- a/statistics/lecture_statistics.tex
+++ b/statistics/lecture_statistics.tex
@@ -4,7 +4,6 @@
 \usepackage{pgf}
 %\usepackage{pgf,pgfarrows,pgfnodes,pgfautomata,pgfheaps,pgfshade} 
 %\usepackage{multimedia}
-\usepackage[ngerman]{babel}
 \usepackage[latin1]{inputenc}
 \usepackage{amsmath}
 \usepackage{bm} 
@@ -86,13 +85,13 @@ Bernstein Center T\"ubingen}
 \end{frame} 
 
 \begin{frame} 
-  \frametitle{Plan}
+  \frametitle{plan}
   \setcounter{tocdepth}{1}
   \tableofcontents 
 
 \end{frame} 
 \begin{frame} 
-  \frametitle{Information \"uber Statistik}
+  \frametitle{information}
   \begin{itemize}
   \item Samuels, M. L., Wittmer, J. A., \& Schaffner,
     A. A. (2010). Statistics for the Life Sciences (4th ed.,
@@ -114,41 +113,41 @@ Bernstein Center T\"ubingen}
 % PCA
 
 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-\section[Präludium]{Präludium}
+\section[Präludium]{Prelude}
 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 
 % ----------------------------------------------------------
 \begin{frame} 
-\frametitle{Meine Erwartungen an Masterstudenten}
+\frametitle{my expectations to this course}
 \begin{itemize}
-\item Interesse und Partizipation
-\item Motivation Konzepte zu verstehen und zu hinterfragen
-\item einen hohen wissenschaftlichen Qualitätsstandard
-\item intellektuelle Redlichkeit
-\item ehrliche Kooperation
+\item interest and participation
+\item motivation to understand and question concepts 
+\item high scientific standard
+\item intellectual honesty
+\item sincere cooperation
 \end{itemize}
 \end{frame}
 
 % ----------------------------------------------------------
 \begin{frame} 
-\frametitle{diese Woche wird ...}
+\frametitle{this week will be ...}
 
 \only<1>{
-\framesubtitle{... kein \sout{Spaß} Zuckerschlecken}
+\framesubtitle{... no \sout{fun} piece of cake}
 \begin{center}
   \includegraphics[height=0.7\textheight]{figs/feeding.jpg}
 \end{center}
 }
 
 \only<2>{
-\framesubtitle{... kein \sout{Spaß} Zuckerschlecken}
+\framesubtitle{... no \sout{fun} piece of cake}
 \begin{center}
   \includegraphics[height=0.7\textheight]{figs/nacho-trainer.jpg}
 \end{center}
 }
 
 \only<3>{
-\framesubtitle{... keine Vorlesung (Bitte!)}
+\framesubtitle{... no lecture (please!)}
 \begin{center}
   \includegraphics[height=0.7\textheight]{figs/soccer.jpg}
 \end{center}
@@ -158,138 +157,131 @@ Bernstein Center T\"ubingen}
 
 % ----------------------------------------------------------
 \begin{frame} 
-\frametitle{Was Ihr diese Woche lernen solltet}
+\frametitle{What you should learn this week}
 \begin{itemize}
-\item Eigenschaften guter Plots
-\item Was ist deskriptive/ inferentielle Statistik?
-\item die generelle Struktur statistischer Tests
-\item Was ist/bedeutet ein p-Wert?
-\item Wie bastele ich mir meinen eigenen Test? 
-\item Wie groß muß mein $n$ sein?
-\item Principal Component Analysis (PCA)
+\item What makes good plots?
+\item What is descriptive/inferential statistics?
+\item What is the general structure of a statistical test?
+\item What does a p-value mean?
+\item How can I build my own tests?
+\item How large should my $n$ be?
+\item What is {\em maximum likelihood} and why is it important?
 \end{itemize}
 \end{frame}
 
 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-\section[deskriptive Statistik, Fehlerbalken \& Plots]{Day 1 -- Deskriptive
-  Statistik, Fehlerbalken und Plots}
+\section[descriptive statistics, errorbars, and plots]{Day 1 -- descriptive statistics, errorbars, and plots}
 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-\subsection{Arten von Daten}
+\subsection{types of data}
 
 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 
 \begin{frame}
-  \frametitle{Datenskalen}
-  \framesubtitle{Welche Datentypen gibt es in der Statistik?}
+  \frametitle{data scales}
+  \framesubtitle{What data types are distinguished in statistics?}
   \Large
-  {\bf Warum sind Datentypen wichtig?}
+  {\bf Why are data types important?}
   \pause
   \begin{itemize}
-  \item Auswahl passender Statistiken
-  \item Auswahl angemessener Plots
-  \item Auswahl von korrekten Tests
+  \item selection of statistics 
+  \item selection of plots
+  \item selection of correct tests
   \end{itemize}
 \end{frame}
 %-------------------------------------------------------------
 
 \begin{frame}
-  \frametitle{Datenskalen}
-  \framesubtitle{Nominalskala (engl. ,,categorial'')}
+  \frametitle{data scales}
+  \framesubtitle{nominal/categorial scale}
   \begin{itemize}
-  \item Eigenschaften wie Zelltyp, Versuchsgruppe
-  \item jede Beobachtung wird eine bestimmten Klasse (Kategorie)
-    zugeordnet
-  \item Die Klassen besitzen keine sinnvolle Ordnung
-  \item  Beispiel: [Zapfen, Stäbchen] vs. [Stäbchen, Zapfen]
+  \item properties like cell type, experimental group (i.e. treatment
+    1, treatment 2, control)
+  \item each observation/sample is put into one category
+  \item there is no reasonable order among the categories
+  \item  example: [rods, cones] vs. [cones, rods]
   \end{itemize}
 \end{frame}
 %-------------------------------------------------------------
 
 \begin{frame}
-  \frametitle{Datenskalen}
-  \framesubtitle{Ordinalskala (engl. ,,ordinal'')}
+  \frametitle{data scales}
+  \framesubtitle{ordinal scale}
   \begin{itemize}
-  \item Wie Nominalskala, nur ist sinnvolles Ordnen m\"oglich
-  \item {\bf aber:} Unterschiede zwischen den Werten bzw. Klassen
-    nicht vergleichbar (keine Abst\"ande)
-  \item Beispiel: Platzierungen, G\"uteklassen, Ratingskalen
+  \item like nominal scale, but there is an order
+  \item {\bf but:} there is no reasonable measure of {\em distance}
+    between the classes
+  \item examples: ranks, ratings
   \end{itemize}
 \end{frame}
 %-------------------------------------------------------------
 
 \begin{frame}
-  \frametitle{Datenskalen}
-  \framesubtitle{Intervallskala (engl. ,,interval'')}
+  \frametitle{data scales}
+  \framesubtitle{interval scale}
   \begin{itemize}
-  \item quantitative/metrische Werte
-  \item Abst\"ande zwischen Werten sind sinnvoll, aber es gibt keine
-    absoluten Nullpunkt
-  \item Beispiel: physikalische Gr\"o{\ss}en wie Temperatur in Grad Celsius
+  \item quantitative/metric values
+  \item reasonable measure of distance between values but no absolute zero
+  \item examples: temperature in $^\circ$C
   \end{itemize}
 \end{frame}
 %-------------------------------------------------------------
 
 \begin{frame}
-  \frametitle{Datenskalen}
-  \framesubtitle{Absolut- oder Verh\"altnisskala (engl. ,,ratio)}
+  \frametitle{data scales}
+  \framesubtitle{absolut/ratio scale}
   \begin{itemize}
-  \item wie Intervallskala, aber mit absolutem Nullpunkt
-  \item Beispiel: Temperatur in Kelvin, Einkommen
+  \item like interval scale but with absolute zero
+  \item example: temperature in $^\circ$K
   \end{itemize}
   \pause
-  \begin{emphasize}{Verh\"altnis der Skalen}
+  \begin{emphasize}{relationsships between scales}
     \begin{itemize}
-    \item Skalen besitzen aufsteigenden Informationsgehalt von
-      Nominal- zu Absolutskala
-    \item Konvertierung ,,abw\"arts'' immer m\"oglich
+    \item scales exhibit increasing information content from nominal
+      to absolute
+    \item conversion  ,,downwards'' always possible
     \end{itemize}
   \end{emphasize}
 \end{frame}
 
 %-------------------------------------------------------------
 \begin{frame}
-  \frametitle{Beispiele aus Neuro-/Kognitionswissenschaften}
+  \frametitle{examples from neuroscience and psychology}
   \begin{itemize}
-  \item {\bf Nominalskala:}\pause 
+  \item {\bf nominal:}\pause 
     \begin{itemize}
-    \item Versuchsgruppenzugeh\"origkeit
-    \item Stimulusklasse
-    \item Zelltyp
+    \item treatment group
+    \item stimulus class
+    \item cell type
     \end{itemize}
 
-  \item {\bf Ordinalskala:} \pause 
+  \item {\bf ordinal:} \pause 
     \begin{itemize}
-    \item Ratings
-    \item Krankheitsstadien
-    \item Zust\"ande eines Ionenkanals
+    \item ratings
+    \item clinical stages of a disease
+    \item states of an ion channel
     \end{itemize}
   \item {\bf Absolut-/Ratioskala:}\pause
     \begin{itemize}
-    \item Feuerrate 
-    \item Membranpotential
-    \item Ionenkonzentration
+    \item firing rate
+    \item membrane potential
+    \item ion concentration
     \end{itemize}
   \end{itemize}
 \end{frame}
 %-------------------------------------------------------------
 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-\subsection{Statistiken}
+\subsection{statistics}
 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 %-------------------------------------------------------------
 \begin{frame}
-  \frametitle{Was ist eine (Test)-Statistik}
-  \begin{definition}{Teststatistik, Pr\"ufwert}
-    \begin{itemize}
-    \item Als {\em Teststatistik} bezeichnet man in der mathematischen
-      Statistik eine Stichprobenfunktion die einer Stichprobe einen
-      Wert zuordnet (z.B. Mittelwert, Median, Standardabweichung,
-      ...).
-
-      \item Als {\em Pr\"ufwert} wird die Realisation einer Teststatistik
-      anhand einer Stichprobe bezeichnet.
-      
-      \source{http://de.wikipedia.org/wiki/Teststatistik}
-    \end{itemize}
+  \frametitle{What is "a statistic"?}
+  \begin{definition}{statistic}
+    A statistic (singular) is a single measure of some attribute of a
+    sample (e.g., its arithmetic mean value). It is calculated by
+    applying a function (statistical algorithm) to the values of the
+    items of the sample, which are known together as a set of data.
+
+    \source{http://en.wikipedia.org/wiki/Statistic}
   \end{definition}
 \end{frame}
 
@@ -297,50 +289,51 @@ Bernstein Center T\"ubingen}
 \begin{frame}
   \frametitle{Beispiele f\"ur Teststatistiken}
   \begin{itemize}
-  \item {\bf Nominalskala:}\pause 
+  \item {\bf nominal:}\pause 
     \begin{itemize}
-    \item Anzahl
-    \item relative H\"aufigkeit
+    \item count
+    \item relative frequency/proportion
     \end{itemize}
 
-  \item {\bf Ordinalskala:} \pause 
+  \item {\bf ordinal:} \pause 
     \begin{itemize}
-    \item Median
-    \item Perzentilen
-    \item Rangkorrelationskoeffizient
+    \item median
+    \item quantile/percentile
+    \item rank correlation 
     \end{itemize}
-  \item {\bf Absolut-/Ratioskala:}\pause
+  \item {\bf absolute/ratio:}\pause
     \begin{itemize}
-    \item Mittelwert
-    \item Varianz/ Standardabweichung
-    \item Pearson Korrelationskoeffizient
+    \item mean
+    \item variance/ standard deviation
+    \item Pearson correlation
     \end{itemize}
   \end{itemize}
 \end{frame}
 
 %-------------------------------------------------------------
 \begin{frame}
-  \frametitle{\"Ubung}
-  \begin{task}{Spearman Rangkorrelationskoeffizient}
+  \frametitle{exercise}
+  \begin{task}{Spearman rank correlation}
     \begin{enumerate}
-    \item Benutze {\tt randi} um zwei 100-dimensionale Vektoren {\tt x,y} mit
-      Zufalls-Integern zwischen $0$ und $10$ zu berechnen. 
-    \item Finde heraus wie man in Matlab den Spearman
-      Rangkorrelationskoeffizient $$\rho = 1- {\frac {6 \sum
-          d_i^2}{n(n^2 - 1)}}$$ berechnet. $d_i = x_i - y_i$ ist die
-      Differenz im Rang der Datenpunkte. 
-    \item Berechne $\rho$ zwischen $x$ und $y$, zwischen $x$ und
-      $y^2$, zwischen $\log(x+1)$ und $y^2$. Berechne auch den
-      \"ublichen (Pearson) Korrelationskoeffizient zwischen diesen
-      Werten. Was kann man beobachten und warum macht das Sinn?
+    \item Use {\tt randi} to generate two  100-dimensional vectors
+      {\tt x,y} of random integers between $0$ and $10$. 
+    \item Find out how to compute the Spearman
+      rank correlation  $$\rho = 1- {\frac {6 \sum
+          d_i^2}{n(n^2 - 1)}}$$ with Matlab. $d_i = x_i - y_i$ is the
+      difference in the rank between the single data points. 
+    \item Compute $\rho$ between $x$ and $y$, between $x$ and
+      $y^2$, between $\log(x+1)$ and $y^2$. 
+    \item Compute the "standard" (Pearson) correlation coefficient
+      between these values. 
+    \item What can you observe and why does it make sense?
     \end{enumerate}
   \end{task}
 \end{frame}
 
 %-------------------------------------------------------------
 \begin{frame}[fragile]
-  \frametitle{\"Ubung - L\"osung}
-  \begin{solution}{Spearman Rangkorrelationskoeffizient}
+  \frametitle{solution}
+  \begin{solution}{Spearman rank correlation }
 \scriptsize
 \begin{lstlisting}
 >>> x = randi(10, 100, 1);
@@ -358,16 +351,16 @@ ans =
 ans =
     0.0551
 \end{lstlisting}
-Der Rangkorrelationskoeffizient \"andert sich nicht bei monotoner
-Transformation der Daten. Daher ist er f\"ur ordinale Daten
-geeignet. Der Pearson Korrelationskoeffizient ist es nicht. 
+The rank correlation does not change under a monotone transformation
+of the data. Therefore, it can be used for ordinal data. The Pearson
+correlation coefficient does not have that property.
   \end{solution}
 \end{frame}
 
 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-\section{Beschreibung und Darstellung von Daten}
+\section{description of data and plotting}
 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-\subsection{Nominalskala}
+\subsection{nominal scale}
 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 %-------------------------------------------------------------
 \begin{frame}[fragile]
@@ -403,7 +396,7 @@ set(gcf, 'PaperPosition',[0.0 0.0 11.7 9.0]);
 \end{lstlisting}
 \end{frame}
 
-%-------------------------------------------------------------
+%----------------------------------------------------------
 \begin{frame}[fragile]
   \frametitle{Darstellung nominaler Daten}
   \framesubtitle{Pie-Chart f\"ur Anzahl/ rel. H\"aufigkeit}
@@ -443,6 +436,11 @@ set(gcf, 'PaperPosition',[0.0 0.0 11.7 9.0]);
 \end{lstlisting}
 \end{frame}
 
+%-------------------------------------------------------------
+\begin{frame}[fragile]
+  \frametitle{Darstellung von Interval-/Absolutskala Daten}
+  
+\end{frame}
 
 \end{document}